Global Xenobiotic Profiling of Rat Plasma Using Untargeted Metabolomics and Background Subtraction-Based Approaches: Method Evaluation and Comparison.

BACKGROUND: Global xenobiotic profiling (GXP) is to detect and structurally characterize all xenobiotics in biological samples using mainly liquid chromatography-high resolution mass spectrometry (LC-HRMS) based methods. GXP is highly needed in drug metabolism study, food safety testing, forensic chemical analysis, and exposome research. For detecting known or predictable xenobiotics, targeted LC-HRMS data processing methods based on molecular weights, mass defects and fragmentations of analytes are routinely employed. For profiling unknown xenobiotics, untargeted and LC-HRMS based metabolomics and background subtraction-based approaches are required. OBJECTIVE: This study aimed to evaluate the effectiveness of untargeted metabolomics and the precise and thorough background subtraction (PATBS) in GXP of rat plasma. METHODS: Rat plasma samples collected from an oral administration of nefazodone (NEF) or Glycyrrhizae Radix et Rhizoma (Gancao, GC) were analyzed by LC-HRMS. NEF metabolites and GC components in rat plasma were thoroughly searched and characterized via processing LC-HRMS datasets using targeted and untargeted methods. RESULTS: PATBS detected 68 NEF metabolites and 63 GC components, while the metabolomic approach (MS-DIAL) found 67 NEF metabolites and 60 GC components in rat plasma. The two methods found 79 NEF metabolites and 80 GC components with 96% and 91% successful rates, respectively. CONCLUSION: Metabolomics methods are capable of GXP and measuring alternations of endogenous metabolites in a group of biological samples, while PATBS is more suited for sensitive GXP of a single biological sample. A combination of metabolomics and PATBS approaches can generate better results in the untargeted profiling of unknown xenobiotics.

Metabolomic Analysis Identifies Differences Between Wild and Domesticated Chili Pepper Fruits During Development (Capsicum annuum L.).

Capsicum spp. members are a rich source of specialized compounds due to their secondary metabolism. Some metabolic pathways have suffered modifications during the domestication process and improvement of agricultural traits. Here, we compared non-targeted LC-MS profiles from several areas: wild accessions (C. annuum L. var. glabriusculum), domesticated cultivars (C. annuum L.), and the F1 progeny of a domesticated, and a wild accession cross (in both directions) throughout seven stages of fruit development of chili pepper fruits. The main detected differences were in glycerophospholipid metabolism, flavone and flavonol biosynthesis, sphingolipid metabolism, and cutin biosynthesis. The domesticated group exhibited a higher abundance in 12'-apo-ß-carotenal, among others capsorubin, and ß-tocopherol. Palmitic acid and derivates, terpenoids, and quercitrin were prevalent in the wild accessions. F1 progeny showed a higher abundance of capsaicin, glycol stearate, and soyacerebroside I. This work supports evidence of the side-affectation of trait selection over the metabolism of chili pepper fruit development. Furthermore, it was also observed that there was a possible heterosis effect over the secondary metabolism in the F1 progeny.

A review of validated biomarkers obtained through metabolomics.

INTRODUCTION: Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.

Dissecting the chloroplast proteome of chickpea (Cicer arietinum L.) provides new insights into classical and non-classical functions.

Chloroplast, the energy organelle unique to plant cells, is a dynamic entity which integrates an array of metabolic pathways and serves as first level for energy conversion for the entire ecological hierarchy. Increasing amount of sequence data and evolution of mass spectrometric approaches has opened up new avenues for opportune exploration of the global proteome of this organelle. In our study, we aimed at generation of a comprehensive catalogue of chloroplast proteins in a grain legume, chickpea and provided a reference proteome map. To accurately assign the identified proteins, purity of chloroplast-enriched fraction was stringently monitored by multiple chemical and immunological indexes, besides pigment and enzyme analyses. The proteome analysis led to the identification of 2451 proteins, including 27 isoforms, which include predicted and novel chloroplast constituents. The identified proteins were validated through their sequence analysis. Extensive sequence based localization prediction revealed more than 50% proteins to be chloroplast resident by at least two different algorithms. Chromosomal distribution of identified proteins across nuclear and chloroplast genome unveiled the presence of 55 chloroplast encoded gene. In depth comparison of our dataset with the non-redundant set of chloroplast proteins identified so far across other species revealed novel as well as overlapping candidates. BIOLOGICAL SIGNIFICANCE: Pulses add large amount of nitrogen to the soil and has very low water footprint and therefore, contributes to fortification of sustainable agriculture. Chickpea is one of the earliest cultivated legumes and serves as an energy and protein source for humans and animals. Chloroplasts are the unique organelles which conduct photosynthesis. Investigation on chloroplast proteome is of particular significance, especially to plant biologists, as it would allow a better understanding of chloroplast function in plants. Generation of a saturated proteome map would not only validate the proteome inventory from its genome sequencing, but also serve as a comprehensive catalogue for future studies. We identified 2451 proteins, encoded by both the nuclear as well as chloroplast genomes, presumably involved in multivariate metabolic processes. The chloroplast deduced proteome and putative chloroplast proteins identified in this study would provide a foundation for future investigation of the expression and function of the chloroplast proteins of chickpea in specific and other crops species in general.

Development of a method for enhancing metabolomics coverage of human sweat by gas chromatography-mass spectrometry in high resolution mode.

Sweat has recently gained popularity as clinical sample in metabolomics analysis as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis that increases chloride levels in sweat. However, the whole composition of sweat is still unknown and there is a lack of analytical strategies for sweat analysis. The aim of the present study was to develop and validate a method for metabolomic analysis of human sweat by gas chromatography-time of flight/mass spectrometry (GC-TOF/MS) in high resolution mode. Thus, different sample preparation strategies were compared to check their effect on the profile of sweat metabolites. Sixty-six compounds were tentatively identified by the obtained MS information. Amino acids, dicarboxylic acids and other interesting metabolites such as myo-inositol and urocanic acid were identified. Among the tested protocols, methyoxiamination plus silylation after deproteinization was the most suited option to obtain a representative snapshot of sweat metabolome. The intra-day repeatability of the method ranged from 0.60 to 16.99% and the inter-day repeatability from 2.75 to 31.25%. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders.

Multiplatform metabolomic fingerprinting as a tool for understanding hypercholesterolemia in Wistar rats.

PURPOSE: The aim was to investigate the impact of hypercholesterolemic diet on the metabolome of male Wistar rats by a multiplatform metabolomic fingerprinting. METHODS: Male Wistar rats were fed with two different diets [control (C) and high-cholesterol diet (HC)-containing 2 % cholesterol and 0.5 % cholic acid]. After 7 weeks of experimental feeding, the rats were euthanized for blood collection and plasma recovery. The metabolite fingerprint was then achieved by applying a multiplatform comprising LC-MS, GC-MS and CE-MS. RESULTS: Multivariate statistical analysis showed a clear separation between the C and HC groups. Individual differences in metabolites were evaluated using univariate statistical analysis, and multiple metabolites were identified and confirmed in the plasma. A global profiling integrates for the first time pathways affected by high-cholesterol diet intake and allowed us to elucidate some of the associated alterations underlying the hypercholesterolemia event in Wistar rats. CONCLUSIONS: HC feeding stimulated the alteration of multiple pathways in Wistar rats, warning of the risk of developing important diseases, which can be modulated by the diet. Further studies are required to investigate the possibilities to revert or ameliorate the negative effects triggered by HC intake.

From sample treatment to biomarker discovery: A tutorial for untargeted metabolomics based on GC-(EI)-Q-MS.

This tutorial provides a comprehensive description of the GC-MS-based untargeted metabolomics workflow including: ethical approval requirement, sample collection and storage, equipment maintenance and setup, sample treatment, monitoring of analytical variability, data pre-processing including deconvolution by free software such as AMDIS, data processing, statistical analysis and validation, detection of outliers and biological interpretation of the results. For each stage tricks will be suggested, pitfalls will be highlighted and advice will be provided on how to get the best from this methodology and technique. In addition, a step-by-step procedure and an example of our in-house library have been included in the supplementary material to lead the user through the concepts described herein. As a case study, an interesting example from one of our experiments at CEMBIO Research Centre is described, presenting an example of the use of this ready-to use protocol for identification of a metabolite that was not previously included in Fiehn commercial target library.

Profiling ribonucleotide modifications at full-transcriptome level: a step toward MS-based epitranscriptomics.

The elucidation of the biological significance of RNA post-transcriptional modifications is hampered by the dearth of effective high-throughput sequencing approaches for detecting, locating, and tracking their levels as a function of predetermined experimental factors. With the goal of confronting this knowledge gap, we devised a strategy for completing global surveys of all ribonucleotide modifications in a cell, which is based on the analysis of whole cell extracts by direct infusion electrospray ionization mass spectrometry (ESI-MS). Our approach eschews chromatographic separation to promote instead the direct application of MS techniques capable of providing detection, differentiation, and quantification of post-transcriptional modifications (PTMs) in complex ribonucleotide mixtures. Accurate mass analysis was used to carry out database-aided identification of PTMs, whereas multistep tandem mass spectrometry (MS(n)) and consecutive reaction monitoring (CRM) provided the necessary structural corroboration. We demonstrated that heat-map plots afforded by ion mobility spectrometry mass spectrometry (IMS-MS) can provide comprehensive modification profiles that are unique for different cell types and metabolic states. We showed that isolated tRNA samples can be used as controlled sources of PTMs in standard-additions quantification. Intrinsic internal standards enable direct comparisons of heat-maps obtained under different experimental conditions, thus offering the opportunity to evaluate the global effects of such conditions on the expression levels of all PTMs simultaneously. This type of comparative analysis will be expected to support the investigation of the system biology of RNA modifications, which will be aimed at exploring mutual correlations of their expression levels and providing new valuable insights into their biological significance.

Optimization study for metabolomics analysis of human sweat by liquid chromatography-tandem mass spectrometry in high resolution mode.

Sweat has recently gained popularity as a potential tool for diagnostics and biomarker monitoring as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis, which increases chloride levels in sweat. The aim of the present study was to develop an analytical method for analysis of human sweat by liquid chromatography-mass spectrometry (LC-Q-TOF MS/MS) in high resolution mode. Thus, different sample preparation strategies and different chromatographic modes (HILIC and C18 reverse modes) were compared to check their effect on the profile of sweat metabolites. Forty-one compounds were identified by the MS/MS information obtained with a mass tolerance window below 4 ppm. Amino acids, dicarboxylic acids and other interesting metabolites such as inosine, choline, uric acid and tyramine were identified. Among the tested protocols, direct analysis after dilution was a suited option to obtain a representative snapshot of sweat metabolome. In addition, sample clean up by C18 SpinColumn SPE cartridges improved the sensitivity of most identified compounds and reduced the number of interferents. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders.