bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2019–12–15
nineteen papers selected by
Sofia Costa, Cold Spring Harbor Laboratory



  1. Biomed Chromatogr. 2019 Dec 11. e4777
      The article describes a systematic study to overcome matrix effect during chromatographic analysis of gemfibrozil, rivastigmine, telmisartan and tacrolimus from biological fluids using LC-ESI-MS/MS. All four methods were thoroughly developed by appropriate choice of analytical column, elution mode and pH of mobile phase for improved chromatography and overall method performance. Matrix effect was assessed by post column analyte infusion, slope of calibration line approach and post extraction spiking. The best chromatographic conditions established were, Acquity BEH C18 (50 × 2.1 mm, 1.7 μm) column with 5.0 mm ammonium acetate, pH 6.0: methanol as the mobile phase under gradient program for gemfibrozil; Luna CN (50 × 2.0 mm, 3 μm) column with a mobile phase consisting of acetonitrile-10 mM ammonium acetate, pH 7.0 (90:10, v/v) for rivastigmine; Inertsustain C18 (100 × 2.0 mm, 5 μm) column using methanol-2.0 mM ammonium formate, pH 5.5 (80: 20, v/v) as the mobile phase for isocratic elution of telmisartan; and Acquity BEH C18 (50 × 2.1 mm, 1.7 μm) with methanol-10 mM ammonium acetate, pH 6.0 (95:5, v/v) as mobile phase for tacrolimus. The methods were thoroughly validated as per EMA and USFDA guidance and were successfully applied for pharmacokinetic studies in healthy subjects.
    Keywords:  Bioanalysis; Ion-suppression; LC-ESI-MS/MS; Pharmacokinetics; Small molecular drugs
    DOI:  https://doi.org/10.1002/bmc.4777
  2. Molecules. 2019 Dec 05. pii: E4459. [Epub ahead of print]24(24):
      Etomidate (ET) is a commonly used sedative-hypnotic agent such as propofol to induce anesthesia, and it is rapidly metabolized to etomidate acid (ETA) in liver. Herein, a simple method to determine ET and ETA in urine simultaneously was developed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). A simple sample preparation method reduced the total analysis time. For all analytes, the separation was achieved in 6.5 min using reversed-phase chromatography with gradient elution. The best separation and detection of ETA was achieved using a porous graphitic carbon column. The column temperature was maintained at 30 °C to improve the efficiency and sensitivity. The calibration curves were linear over the concentration ranges of 0.4-120.0 ng/mL (ET) and 1.0-300.0 ng/mL (ETA), obtained with a weighting factor of 1/x2. The coefficients of determination (r2) were greater than 0.9958. The lower limits of quantification were 0.4 ng/mL (ET) and 1.0 ng/mL (ETA), intra-day (n = 6) and inter-day (n = 24) precision values for all compounds were less than 10.2% and 8.4%, respectively, while the intra- and inter-day accuracies were in the -9.9-2.9%, and -7.0-0.6%. The applicability of the method was examined by analyzing the urine samples obtained from ET users.
    Keywords:  LC-MS/MS; dilute and shoot; etomidate; etomidate acid; metabolite; urine
    DOI:  https://doi.org/10.3390/molecules24244459
  3. J Chromatogr B Analyt Technol Biomed Life Sci. 2019 Nov 27. pii: S1570-0232(19)31269-3. [Epub ahead of print]1136 121884
      A method for the simultaneous quantification of B vitamins and related amines in one-carbon (1C) metabolism would benefit the study of diet and genetic/epigenetic regulation of mammalian development and health. We present a validated method for the simultaneous quantitative analysis of 13 B vitamers and four related 1C-pathway amine intermediates in liver using hydrophilic interaction chromatography (HILIC) coupled to electrospray ionization tandem mass spectrometry. Frozen sheep liver samples (50 mg) were homogenized in cold 50% acetonitrile containing 1% acetic acid with the addition of two isotope labelled internal standards. Hot acid hydrolysis was applied to release the protein-bound forms. The separation of 17 analytes was achieved using a pHILIC column with a total run time of 13 min. Detection was achieved in electrospray positive ionisation mode. Limits of detection for the majority of analytes were within the range of 0.4-3.2 pmol/g. The method was applied to 266 sheep liver samples and revealed that adenosylcobalamin, methylcobalamin, pyridoxic acid, flavin adenine dinucleotide and thiamine were the major forms of the B vitamers present with pyridoxal 5'-phosphate and thiamine pyrophosphate being detected at lower concentrations. Trimethylglycine and methylglycine were the predominant 1C-related amines measured. As anticipated, the B vitamin status of individuals varied considerably, reflecting dietary and genetic variation in our chosen outbred model species. This method offers a simple sample extraction procedure and provides comprehensive coverage of B vitamins coupled with good sensitivity and reliability.
    Keywords:  Amines; B vitamins; HILIC; Mass spectrometry; One-carbon metabolism; Sheep liver
    DOI:  https://doi.org/10.1016/j.jchromb.2019.121884
  4. J Lipid Res. 2019 Dec 09. pii: jlr.RA119000311. [Epub ahead of print]
      Bile acids (BAs) serve multiple biological functions, ranging from absorption of lipids and fat-soluble vitamins, to serving as signaling molecules through the direct activation of dedicated cellular receptors. Synthesized by both host and microbial pathways, BAs are increasingly appreciated to participate in the regulation of numerous pathways relevant to metabolic diseases including lipid and glucose metabolism, energy expenditure and inflammation, pathways relevant to metabolic diseases.  Quantitative analyses of BAs in biological matrices can be problematic due to their unusual and diverse physicochemical properties, making optimization of a method that shows good accuracy, precision, efficiency of extraction, and minimized matrix effects across structurally distinct human and murine BAs challenging.  Herein we develop and clinically validate a stable isotope dilution liquid chromatography-tandem mass spectrometry (LC/MS/MS) method for the quantitative analysis of numerous primary and secondary BAs in both human and mouse biological matrices. We also utilize this tool to investigate gut microbiota participation in generation of structurally specific BAs in both humans and mice. We examine circulating levels of specific BAs and in a clinical case-control study of age- and gender-matched type 2 diabetics (T2DM) versus non-diabetics. BAs whose circulating levels are associated with T2DM include numerous 12α-hydroxyl BAs (taurocholic acid, taurodeoxycholic acid, glycodeoxycholic acid, deoxycholic acid and 3-ketodeoxycholic acid), while taurohyodeoxycholic acid was negatively associated with diabetes. The LC/MS/MS based platform described should serve as a robust, high throughput investigative tool for studying the potential involvement of structurally specific BAs and the gut microbiome on both physiological and disease processes.
    Keywords:  Bile acids and salts; Diabetes; Mass spectrometry; Microbial metabolome; Steroid hormones
    DOI:  https://doi.org/10.1194/jlr.RA119000311
  5. Bioanalysis. 2019 Nov;11(21): 1967-1980
      Aim: Advancements in RNA interference therapeutics have triggered development of improved bioanalytical methods for oligonucleotide metabolite profiling and high-throughput quantification in biological matrices. Results & methodology: HPLC coupled with high-resolution mass spectrometry (LC-HRMS) methods were developed to investigate the metabolism of a REVERSIR™ molecule in vivo. Plasma and tissue samples were extracted using solid-phase extraction followed by LC-HRMS analysis for metabolite profiling and quantification. The method was qualified from 10 to 5000 ng/ml (plasma) and 100 to 50000 ng/g (liver and kidney). In rat liver, intra and interday accuracy ranged from 80.9 to 118.5% and 88.4 to 111.9%, respectively, with acceptable precision (<20% CV). Conclusion: The LC-HRMS method can be applied for metabolite profiling and quantification of oligonucleotides in biological matrices.
    Keywords:  RNAi; mass spectrometry; metabolite profiling; oligonucleotide; pharmacokinetic; siRNA; small interfering RNA
    DOI:  https://doi.org/10.4155/bio-2019-0137
  6. Talanta. 2020 Feb 01. pii: S0039-9140(19)31090-2. [Epub ahead of print]208 120457
      Inductively Coupled Plasma Mass Spectrometry (ICP-MS) hyphenated to High Performance Liquid Chromatography (HPLC) and Ion Chromatography (IC) are widely used for simultaneous speciation of arsenic (As). Longer retention time resulting in a slow separation is the major drawback of these existing approaches. Besides, fast separations achieved from HPLC based methods have always resulted in poor resolution and baseline separation between peaks. For the first time, the present study aimed to improve the existing HPLC related methods in order to develop a fast analytical protocol based on Ultra-High Performance Liquid Chromatography (UHPLC) hyphenated to ICP-MS detection for simultaneous separation and quantification of arsenite (As(III)), arsenate (As(V)), dimethylarsonate (DMA(V)) and monomethylarsenate (MMA(V)). Two types of ammonium-based mobile phases (i.e. NH4H2PO4 and NH4NO3) were examined at different eluent concentrations and pH to choose the most effective eluent system. Results demonstrated that the mixed mobile phase containing 8.5 mM of NH4H2PO4 and NH4NO3 (1:1) at pH 6.0 is the most effective eluent achieving the separation of As species with improved resolutions within 5 min which is almost a double saving in analysis time per sample compared to the existing methods (9-15 min). Faster separation is analytically cost effective in terms of ICP-MS running cost and energy consumption. Unlike HPLC, UHPLC did not generate a higher column back pressure with increasing flow rate up to 2.5 mL/min resulting in a faster separation with excellent resolution of peaks. Limits of detection for As species were in the range of 0.3-0.5 μg/L. The proposed method was applied to quantify As species present in commercially available rice varieties in Australia and Sri Lanka. Results of speciation analysis indicated that As(III) is the dominant species, ranging from 53 to 100% in the rice grains. The proposed analytical protocol based on UHPLC-ICP-MS provided an accurate and reliable identification and quantification of As species with the advantages of rapid separation, excellent resolution, and low detection limits. Such a recent trend in fundamental research could be a turning point for future environmental and biological research to further improve this strategy for the speciation of other toxic metal(loid)s in food, water and biological samples.
    Keywords:  Anion exchange; Arsenic speciation; Resolution; Rice; Ultra-high performance; hyphenate
    DOI:  https://doi.org/10.1016/j.talanta.2019.120457
  7. Wiley Interdiscip Rev Syst Biol Med. 2019 Dec 09. e1472
      Unique features of cyanobacteria (e.g., photosynthesis and nitrogen fixation) make them potential candidates for production of biofuels and other value-added biochemicals. As prokaryotes, they can be readily engineered using synthetic and systems biology tools. Metabolic engineering of cyanobacteria for the synthesis of desired compounds requires in-depth knowledge of central carbon and nitrogen metabolism, pathway fluxes, and their regulation. Metabolomics and fluxomics offer the comprehensive analysis of metabolism by directly characterizing the biochemical activities of cells. This information is acquired by measuring the abundance of key metabolites and their rates of interconversion, which can be achieved by labeling cells with stable isotopes, quantifying metabolite pool sizes and isotope incorporation by gas chromatography/liquid chromatography-mass spectrometry GC/LC-MS or nuclear magnetic resonance (NMR), and mathematical modeling to estimate in vivo metabolic fluxes. Herein, we review progress that has been made to adapt metabolomics and fluxomics tools to examine model cyanobacterial species. We summarize the application of metabolic flux analysis (MFA) strategies to identify metabolic bottlenecks that can be targeted to boost cell growth, improve stress tolerance, or enhance biochemical production in cyanobacteria. Despite the advances in metabolomics, fluxomics, and other synthetic and systems biology tools during the past years, further efforts are required to increase our understanding of cyanobacterial metabolism in order to create efficient photosynthetic hosts for the production of value-added compounds. This article is categorized under: Laboratory Methods and Technologies > Metabolomics Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods.
    Keywords:  cyanobacteria; fluxomics; mass spectrometry; metabolic flux; metabolomics
    DOI:  https://doi.org/10.1002/wsbm.1472
  8. Bioanalysis. 2019 Nov;11(21): 1983-1992
      There are a few different bioanalytical approaches that have been used for the quantification of siRNA in biological matrices, such as S1 nuclease protection 'cutting ELISA', fluorescent probe hybridization HPLC, HPLC UV, LC-MS/high-resolution accurate-mass (HRAM) and LC-MS/MS. We have developed and validated plasma assays for several oligonucleotides such as GalNAc-conjugated siRNA, using uHPLC and high-resolution mass spectrometer by TOF detection. Although the molecular weights are in the range of 7000-9000, we were able to meet the same assay acceptance criteria as for the small molecules based on regulatory bioanalytical method validation guidance. The antisense strand and the sense strand can both be monitored. The method was also used in the tissue lysate matrices without a full validation.
    Keywords:  HRMS; LC–TOF–MS; antisense; clarity OTX plates and lysis buffer; isotopic envelope; oligonucleotide; pharmacokinetics of siRNA; siRNA in biological matrices; siRNA metabolite quantitation; solid-phase extraction
    DOI:  https://doi.org/10.4155/bio-2019-0134
  9. Anal Bioanal Chem. 2019 Dec 10.
      Lipids are amongst the most important organic compounds in living organisms, where they serve as building blocks for cellular membranes as well as energy storage and signaling molecules. Lipidomics is the science of the large-scale determination of individual lipid species, and the underlying analytical technology that is used to identify and quantify the lipidome is generally mass spectrometry (MS). This review article provides an overview of the crucial steps in MS-based lipidomics workflows, including sample preparation, either liquid-liquid or solid-phase extraction, derivatization, chromatography, ion-mobility spectrometry, MS, and data processing by various software packages. The associated concepts are discussed from a technical perspective as well as in terms of their application. Furthermore, this article sheds light on recent advances in the technology used in this field and its current limitations. Particular emphasis is placed on data quality assurance and adequate data reporting; some of the most common pitfalls in lipidomics are discussed, along with how to circumvent them.
    Keywords:  Chromatography; LC-MS; Lipidomics; Mass spectrometry; Shotgun lipidomics
    DOI:  https://doi.org/10.1007/s00216-019-02241-y
  10. J Proteome Res. 2019 Dec 10.
      Identification of new biomarkers may help to early diagnosis of inflammatory bowel disease (IBD). In this study, ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC - QTOF - MS) were used to analyze the untargeted lipidomics and compare plasma lipid profiles between IBD patients and control subjects. The principal component analysis and partial least-squares-discriminant analysis were carried out to distinguish IBD patients from control subjects. Using univariate and multivariate analysis, 55 significantly different metabolites from five lipid classes, fatty acyls (n=19), glycerophospholipids (n=5), prenol lipids (n=10), sphingolipids (n=2), and sterol lipids (n=19) were identified. Forty four of the 55 metabolites were analyzed by receiver operating characteristic (ROC) curve and of area under curve (AUC) > 0.80. After validation in an independent cohort, IBD patients were differentiated from the control subjects by significantly altered plasma level of Palmitic acid, 7alpha,25-dihydroxycholesterol, 20-hydroxyeicosatetraenoic (HETE) -d6, (+/-)5,6- epoxy-eicosatrienoic acid (EpETrE), docosahexaenoic acid (DHA), 9-heptadecylenic acid, Lactucaxanthin, alpha-Carotene, Traumatic acid, and Neoquassin with both sensitivity and specificity above 80%. Pathway analysis suggested that IBD dysregulation was related to the biosynthesis of primary bile acid, the metabolism of arachidonic acid, the metabolism of sphingolipid, fatty acid elongation and glycerophospholipid metabolism. Our results suggest the lipidomic profiling of patients plasma could be a potential method for IBD diagnosis.
    DOI:  https://doi.org/10.1021/acs.jproteome.9b00440
  11. J Neurol. 2019 Dec 10.
       BACKGROUND: Brain tumors cause significant morbidity and mortality due to rapid progression and high recurrence risks. Reliable biomarkers to improve diagnosis thereof are desirable.
    OBJECTIVE: This work aimed to identify panels of biomarkers for diagnostic purposes using cerebrospinal fluid (CSF)-based metabolomics.
    METHODS: A cohort of 163 histologically-proven patients with brain disorders was involved. Comprehensive CSF-based metabolomics was achieved by liquid chromatography-quadrupole time-of-flight spectrometric (LC-Q/TOF-MS) and multivariate statistical analyses. The diagnostic performance of the metabolic markers was evaluated using receiver operating characteristic curves.
    RESULTS: A total of 508 ion features were detected by the LC-Q/TOF-MS analysis, of which 27 metabolites were selected as diagnostic markers to discriminate different brain tumor types. The area under the curve (AUC) was 0.91 for lung adenocarcinoma patients with brain metastases (MBT) vs. lung adenocarcinoma patients without brain metastases (NMBT), 0.83 for primary central nervous system lymphoma (PCNSL) vs. secondary central nervous system involvement of systemic lymphoma (SCNSL), 0.77 for PCNSL vs. MBT, 0.87 for SCNSL vs. MBT, 0.86 for MBT vs. nontumorous brain diseases (NT), and 0.80 for PCNSL vs. NT. Perturbed metabolic pathways between the comparisons related mainly to amino acids and citrate metabolism.
    CONCLUSIONS: CSF-based metabolomics to a large extent reliably identifies significant metabolic differences between different brain tumors and shows great potential for diagnosis of brain tumors.
    Keywords:  Brain tumors; CNS lymphoma; Cerebrospinal fluid; Diagnosis; Metabolomics
    DOI:  https://doi.org/10.1007/s00415-019-09665-7
  12. Talanta. 2020 Feb 01. pii: S0039-9140(19)31061-6. [Epub ahead of print]208 120428
      Sweat is gaining popularity in clinical metabolomics as this biofluid is non-invasively sampled and its composition is modified by several pathologies. There is a lack of standardized strategies for collection of human sweat. Most studies have been carried out with fresh sweat collected after stimulation. A promising and simple alternative is sampling dry sweat by a solid support impregnated with a suited solvent. This research was aimed at comparing the metabolomics coverage provided by dry sweat collected by two solid supports (gauzes and filter papers) impregnated with different solvents. The dissolved dry sweat was analyzed by a dual approach: gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Among the tested sampling strategies, filter paper impregnated with 1:1 (v/v) ethanol‒phosphate buffer resulted the combination providing the highest metabolomics coverage (tentative identification of one hundred seventy-five compounds). Dry and fresh sweat were compared by using pools from the same individuals to evaluate compositional differences. Families of metabolites such as carnitines, sphingolipids and N-acyl-amino acids, among others, were exclusively identified in dry sweat. Comparison of both samples allowed concluding that dry sweat is better for analysis of low polar metabolites and fresh sweat is more suited for polar compounds. As most of the identified metabolites are involved in key biochemical pathways, this study opens interesting possibilities to the use of dry sweat as a source of metabolite markers for specific disorders. Sampling of dry sweat could provide a standardized approach for collection of this biofluid, thus overcoming the variability limitations of fresh sweat.
    Keywords:  Dry sweat metabolome; Gas chromatography; Liquid chromatography; Mass spectrometry; Metabolomics analysis; Sampling protocol
    DOI:  https://doi.org/10.1016/j.talanta.2019.120428
  13. Free Radic Biol Med. 2019 Dec 05. pii: S0891-5849(19)31565-5. [Epub ahead of print]
      Coenzyme Q (CoQ) is an essential cofactor, primarily found in the mitochondrial inner membrane where it functions as an electron carrier in the respiratory chain, and a lipophilic antioxidant. The redox state of the CoQ pool is the ratio of its oxidised (ubiquinone) and reduced (ubiquinol) forms, and is a key indicator of mitochondrial bioenergetic and antioxidant status. However, the role of CoQ redox state in vivo is poorly understood, because determining its value is technically challenging due to redox changes during isolation, extraction and analysis. To address these problems, we have developed a sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay that enables us to extract and analyse both the CoQ redox state and the magnitude of the CoQ pool with negligible changes to redox state from small amounts of tissue. This will enable the physiological and pathophysiological roles of the CoQ redox state to be investigated in vivo.
    Keywords:  CoQ(10); CoQ(9); Coenzyme Q; Mass spectrometry; Mitochondria; Oxidative stress; Redox state
    DOI:  https://doi.org/10.1016/j.freeradbiomed.2019.11.028
  14. Oxid Med Cell Longev. 2019 ;2019 4851323
      Glycation, oxidation, nitration, and crosslinking of proteins are implicated in the pathogenic mechanisms of type 2 diabetes, cardiovascular disease, and chronic kidney disease. Related modified amino acids formed by proteolysis are excreted in urine. We quantified urinary levels of these metabolites and branched-chain amino acids (BCAAs) in healthy subjects and assessed changes in early-stage decline in metabolic, vascular, and renal health and explored their diagnostic utility for a noninvasive health screen. We recruited 200 human subjects with early-stage health decline and healthy controls. Urinary amino acid metabolites were determined by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry. Machine learning was applied to optimise and validate algorithms to discriminate between study groups for potential diagnostic utility. Urinary analyte changes were as follows: impaired metabolic health-increased N ε -carboxymethyl-lysine, glucosepane, glutamic semialdehyde, and pyrraline; impaired vascular health-increased glucosepane; and impaired renal health-increased BCAAs and decreased N ε -(γ-glutamyl)lysine. Algorithms combining subject age, BMI, and BCAAs discriminated between healthy controls and impaired metabolic, vascular, and renal health study groups with accuracy of 84%, 72%, and 90%, respectively. In 2-step analysis, algorithms combining subject age, BMI, and urinary N ε -fructosyl-lysine and valine discriminated between healthy controls and impaired health (any type), accuracy of 78%, and then between types of health impairment with accuracy of 69%-78% (cf. random selection 33%). From likelihood ratios, this provided small, moderate, and conclusive evidence of early-stage cardiovascular, metabolic, and renal disease with diagnostic odds ratios of 6 - 7, 26 - 28, and 34 - 79, respectively. We conclude that measurement of urinary glycated, oxidized, crosslinked, and branched-chain amino acids provides the basis for a noninvasive health screen for early-stage health decline in metabolic, vascular, and renal health.
    DOI:  https://doi.org/10.1155/2019/4851323
  15. BMC Bioinformatics. 2019 Dec 10. 20(1): 649
       BACKGROUND: Studies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. It is widely recognized that integrative omics analysis holds the promise to unlock novel and actionable biological insights into health and disease. Integration of multi-omics data remains challenging, however, and requires combination of several software tools and extensive technical expertise to account for the properties of heterogeneous data.
    RESULTS: This paper presents the miodin R package, which provides a streamlined workflow-based syntax for multi-omics data analysis. The package allows users to perform analysis of omics data either across experiments on the same samples (vertical integration), or across studies on the same variables (horizontal integration). Workflows have been designed to promote transparent data analysis and reduce the technical expertise required to perform low-level data import and processing.
    CONCLUSIONS: The miodin package is implemented in R and is freely available for use and extension under the GPL-3 license. Package source, reference documentation and user manual are available at https://gitlab.com/algoromics/miodin.
    Keywords:  Data analysis; Data integration; Multi-omics; Transparency
    DOI:  https://doi.org/10.1186/s12859-019-3224-4
  16. Genes (Basel). 2019 Dec 05. pii: E1011. [Epub ahead of print]10(12):
      Growing evidence suggests that aberrant energy metabolism could play an important role in the pathogenesis of amyotrophic lateral sclerosis (ALS). Despite this, studies applying advanced technologies to investigate energy metabolism in ALS remain scarce. The rapidly growing field of metabolomics offers exciting new possibilities for ALS research. Here, we review existing and emerging metabolomic tools that could be used to further investigate the role of metabolism in ALS. A better understanding of the metabolic state of motor neurons and their surrounding cells could hopefully result in novel therapeutic strategies.
    Keywords:  amyotrophic lateral sclerosis; energy metabolism; mass spectrometry; metabolic dysfunction; metabolomics; motor neuron
    DOI:  https://doi.org/10.3390/genes10121011
  17. Chem Res Toxicol. 2019 Dec 10.
      The importance of adsorption, distribution, metabolism excretion and toxicity (ADMET) analysis is expected to grow substantially due to recent failures in detecting severe toxicity issues of new chemical entities during preclinical/clinical development. Traditionally, safety risk assessment studies for humans have been conducted in animals during advanced preclinical or clinical phase of drug development. However, potential drug toxicity in humans now needs to be detected in the drug discovery process as soon as possible without reliance on animal studies. The 'omics', such as genomics, proteomics and metabolomics, have recently entered pharmaceutical research in both drug discovery and drug development, but at the best of our knowledge no applications in high-throughput safety risk assessment have been attempted so far. This paper reports an innovative method to anticipate adverse drug effects in an early discovery phase based on lipid fingerprints using human three-dimensional (3D) microtissues. The risk of clinical hepatotoxicity potential was evaluated for a dataset of 22 drugs belonging to five different therapeutic chemical classes and with various drug-induced liver injury effect. The treatment of microtissues with repeated doses of each drug allowed collecting lipid fingerprints for five time points (2, 4, 7, 9 and 11 days), and multivariate statistical analysis was applied to search for correlations with the hepatotoxic effect. The method allowed clustering of the drugs based on their hepatotoxic effect, and the observed lipid impairments for a number of drugs was confirmed by literature sources. Compared to traditional screening methods, here multiple interconnected variables (lipids) are measured simultaneously, providing a snapshot of the cellular status from the lipid perspective at a molecular level. Applied here to hepatotoxicity, the proposed workflow can be applied to several tissues, being tridimensional microtissues from various origins.
    DOI:  https://doi.org/10.1021/acs.chemrestox.9b00364
  18. Gigascience. 2019 12 01. pii: giz143. [Epub ahead of print]8(12):
       BACKGROUND: Mass spectrometry imaging is increasingly used in biological and translational research because it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired datasets are large and complex and often analyzed with proprietary software or in-house scripts, which hinders reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many mass spectrometry imaging (MSI) researchers.
    FINDINGS: We have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Furthermore, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research.
    CONCLUSION: The Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access, together with high levels of reproducibility and transparency.
    Keywords:  Galaxy; MALDI imaging; computational workflows; mass spectrometry imaging; metabolomics; proteomics; reproducibility; spatially resolved mass spectrometry
    DOI:  https://doi.org/10.1093/gigascience/giz143
  19. Metabolomics. 2019 Dec 10. 16(1): 5
       INTRODUCTION: Meta-analysis is the cornerstone of robust biomedical evidence.
    OBJECTIVES: We investigated whether statistical reporting practices facilitate metabolomics meta-analyses.
    METHODS: A literature review of 44 studies that used a comparable platform.
    RESULTS: Non-numeric formats were used in 31 studies. In half of the studies, less than a third of all measures were reported. Unadjusted P-values were missing from 12 studies and exact P-values from 9 studies.
    CONCLUSION:  Reporting practices can be improved. We recommend (i) publishing all results as numbers, (ii) reporting effect sizes of all measured metabolites and (iii) always reporting unadjusted exact P-values.
    Keywords:  Integration; Meta analysis; Metabolic profiles; NMR; Reporting; Summary statistics
    DOI:  https://doi.org/10.1007/s11306-019-1626-y