Updates in metabolomics tools and resources: 2014-2015

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources—in the form of tools, software, and databases—is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table

Targeted LC-MS/MS-based metabolomics and lipidomics on limited hematopoietic stem cell numbers

Metabolism is important for the regulation of hematopoietic stem cells (HSCs) and drives cellular fate. Due to the scarcity of HSCs, it has been technically challenging to perform metabolome analyses gaining insight into HSC metabolic regulatory networks. Here, we present two targeted liquid chromatography–mass spectrometry approaches that enable the detection of metabolites after fluorescence-activated cell sorting when sample amounts are limited. One protocol covers signaling lipids and retinoids, while the second detects tricarboxylic acid cycle metabolites and amino acids. For complete details on the use and execution of this protocol, please refer to Schönberger et al. (2022)

Roles of type II H+-PPases and PPsPase1/PECP2 in early developmental stages and PPi homeostasis of Arabidopsis thaliana

The regulation of intracellular pyrophosphate (PPi) level is crucial for proper morphogenesis across all taxonomic kingdoms. PPi is released as a byproduct from ~200 metabolic reactions, then hydrolyzed by either membrane-bound (H+-PPase) or soluble pyrophosphatases (PPases). In Arabidopsis, the loss of the vacuolar H+-PPase/FUGU5, a key enzyme in PPi homeostasis, results in delayed growth and a number of developmental defects, pointing to the importance of PPi homeostasis in plant morphogenesis. The Arabidopsis genome encodes several PPases in addition to FUGU5, such as PPsPase1/PECP2, VHP2;1 and VHP2;2, although their significance regarding PPi homeostasis remains elusive. Here, to assess their contribution, phenotypic analyses of cotyledon aspect ratio, palisade tissue cellular phenotypes, adaxial side pavement cell complexity, stomatal distribution, and etiolated seedling length were performed, provided that they were altered due to excess PPi in a fugu5 mutant background. Overall, our analyses revealed that the above five traits were unaffected in ppspase1/pecp2, vhp2;1 and vhp2;2 loss-of-function mutants, as well as in fugu5 mutant lines constitutively overexpressing PPsPase1/PECP2. Furthermore, metabolomics revealed that ppspase1/pecp2, vhp2;1 and vhp2;2 etiolated seedlings exhibited metabolic profiles comparable to the wild type. Together, these results indicate that the contribution of PPsPase1/PECP2, VHP2;1 and VHP2;2 to PPi levels is negligible in comparison to FUGU5 in the early stages of seedling development

Metabolomics Data Processing and Data Analysis—Current Best Practices

Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme “Best Practices in Metabolomics Data Analysis”. Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows

Exploring the diagnostic potential of extracellular metabolites produced by oral pathogen Porphyromonas gingivalis

Periodontitis, one of the most prevalent chronic inflammatory diseases, is induced by periodontal bacteria. Porphyromonas gingivalis, recognized as the "keystone pathogen," is hypothesized to orchestrate the dysbiotic shift of the polymicrobial community, thereby initiating periodontitis. The intricate interactions between P. gingivalis and the host could provide insights into the transition between health and disease states. This study aims to examine the extracellular metabolome produced by P. gingivalis under conditions simulating health and disease states, and to explore the potential of P. gingivalis-derived extracellular metabolites as biomarkers for disease diagnosis and prediction. Employing untargeted and targeted metabolomics techniques, we initially characterized distinct extracellular metabolite profiles produced by P. gingivalis, detecting 24,773 annotated metabolites under various haemoglobin levels corresponding to different disease stages. Among the top-ranked annotated metabolites contributing to the variances between groups, kynurenic acid, tryptophan, indole, and protoporphyrin IX (PPIX) were identified. These identified extracellular metabolites are proposed to contribute to disease initiation and progression through several possible mechanisms, including bacterial cross-feeding, biofilm regulation, and immune modulation. To further explore the potential of P. gingivalis-derived extracellular metabolites as diagnostic and predictive biomarkers for periodontitis, a prediction model, based on logistic regression combined with a Receiver Operator Characteristic (ROC) curve, was developed. The model, utilizing tryptophan and PPIX as diagnostic markers, demonstrated high accuracy in distinguishing the active disease cohort from both the healthy control and post-treatment cohorts. The findings of this study suggest a promising periodontitis prediction model based on P. gingivalis-derived extracellular metabolites

Metabolomic Applications in Animal Science

Metabolomics has been a useful method for various study fields. However, its application in animal science does not seem to be sufficient. Metabolomics will be useful for various studies in animal science: Animal genetics and breeding, animal physiology, animal nutrition, animal products (milk, meat, eggs, and their by-products) and their processing, livestock environment, animal biotechnology, animal behavior, and animal welfare. More application examples and protocols for animal science will promote more motivation to use metabolomics effectively in the study field. Therefore, in this Special Issue, we introduced some research and review articles for “Metabolomic Applications in Anmal Science”. The main methods used were mass spectrometry or nuclear magnetic resonance spectroscopy. Not only a non-targeted, but also a targeted, analysis of metabolites is shown. The topics include dietary and pharmacological interventions and protocols for metabolomic experiments

The effect of charge location in ion mobility mass spectrometry for small molecule analytes

In travelling wave IM-MS an electric field is applied across the IMS cell and analyte collisions with the inert gas give rise to a relationship between the drift time and the molecular shape and overall charge. Recent findings show near baseline IMS separation (R>1) where shape and overall charge appear not to explain the IMS separation. Multiple ion mobility peaks are observed for a single m/z including the fluoroquinolone antibiotics norfloxacin and lomefloxacin, the pesticide indoxacarb and a number of steroids

Metabolic Profiling of Human Germinal Center: Unraveling Distinct Carbohydrate Dependencies in Germinal Center B cells

Background and Objective Despite the well-established role of germinal centers (GCs) ln long-lived protective immunity, insight into the metabolic and energetic compartmentalization of GC B cells (GCBCs) within the distinct functional districts of GCs remains unclear. This PhD project alms to evaluate the spatial organization of metabolic and energetic dynamics within human GCs. Hypothesis Three main immune reactions occur ln GCs: l) clonal expansion, ll) BCR diversification and lll) BCR-affinity-based selection. These immune reactions spatially segregate, with proliferation and BCR diversification ln the dark zone (DZ) and BCR-affinity-based selection ln the light zone (LZ). Given the differences ln immune reactions and cell-cycle progression status across these functional microenvironments, we hypothesized that distinct metabolic programs operate ln association with these zones to optimize the outcomes of these immune events. Results Increased Glucose Transporter l (GLUTl) expression and enhanced 2NBDG uptake were observed ln GCBCs. Multiplex imaging analysis on human tonsillar sections revealed a polarized distribution of GLUTl towards the LZ. Consistently, glycolysis and glycolysios-anabolism predominantly operated ln the LZ ln non-dividing B cells. Heightened LDHA and MCTl expression was observed ln mitotically active DZ B cells. Furthermore, by combining imaging analysis with mass-spectrometry, we found that LDHA-lactate production ln GCs not only sustained glycolysis but was also enhanced among dividing B cells ln the DZ. Despite increased LDHA-lactate production and significant differential expression of MDH and PCK ln GCBCs, perturbations of upstream gluconeogenic reactions ln GLUTldim/low GCBCs did not impact the TCA cycle intermediates profile. Quantitative imaging analysis revealed that LDHB polarized ln the DZ and was found highly coexpressed with MCTl ln dividing DZ B cells. Blockade of mitochondrial pyruvate uptake resulted ln a pronounced reduction ln oxygen consumption ln GCBCs. Conclusions Our analysis showed that ln GCs, a heterogeneous carbohydrate dependence drives distinct metabolic programs associated with the different immune events occurring ln the GC functional compartments. -- Contexte et Objectif Malgré le fait que la connaissance du rôle des centres germinatifs (CG) dans l'immunité protectrice à long terme soit bien établie la compréhension de la compartimentalisation métabolique et énergétique des lymphocytes B des centres germinatifs (LCBCG) au sel des différentes zones fonctionnelles des CG demeure floue Ce projet de doctorat a pour objectif d'évaluer l'organisation spatiale des dynamiques métaboliques et énergétiques au sein des CG humains. Hypothèse Trois principales réactions immunitaires se propulsent dans les GC: l) expansion clonale, ll) diversification des récepteurs B (BCR) et lll) sélection basée sur l'affinité des BCR. Ces réactions immunitaires se séparent spatialement, avec la prolifération et la diversification des BCR dans la zone sombre (dark zone DZ) et la sélection basée sur l'affinité des BCR dans la zone claire (light zone LZ). Etant données les différences dans les réactions immunitaires et le statut de progression du cycle cellulaire à travers ces microenvironnements fonctionnels, nous avons émis l'hypothèse que des programmes métaboliques distincts fonctionnent en association avec ces zones pour optimiser les résultats de ces événements immunitaires. Résultats L'expression accrue de GLUTI et l'augmentation de la capture de 2NBDG ont été observées dans les LCBCG. L'analyse d'imagerie multiplexe sur des sections de tonsilles humanes a révélé une distribution polarisée de GLUTl vers la LZ. De plus, la glycolyse et la glycolyse-anabolisme fonctionnaient principalement dans la LZ chez les cellules B non divisantes. Une expression accrue de LDHA et de MCTl a été observée chez les cellules B de la DZ actives mitotiquement. De plus, en combinant l'analyse d'imagerie avec le spectromètre de masse, nous avons constaté que la production de lactate par LDHA dans les CG soutenait non seulement la glycolyse mais était également démultipliée parmi les cellules B en division dans la DZ. Malgré une production accrue de LDHA- lactate et une expression différentielle significative de MDH et de PCK dans les LCBCG, les perturbations des réactions gluconéogéniques en amont dans les LCBCG GLUT1dim/low n’avaient pas d'impact sur le profil des intermédiaires du cycle de l'acide citrique (TCA). L'analyse d'imagerie quantitative a révélé que LDHB était polarisé dans la DZ et était fortement coexprimé avec MCTl chez les cellules B en division de la DZ. Le blocage de la capture mitochondriale du pyruvate entraînait une forte réduction de la consommation d'oxygène chez les LCBCG. Conclusions Notre analyse a montré qu'au sein des CG, une dépendance hétérogène aux glucides conduit à des programmes métaboliques distincts associés aux différents événements immunitaires survenant dans les compartiments fonctionnels des CG