MassTRIX: mass translator into pathways

From sound check to encore: A journey through high-resolution mass spectrometry-based food analyses and metabolomics

This manuscript presents a comprehensive review of high-resolution mass spectrometry in the field of food analysis and metabolomics. We have followed the historical evolution of metabolomics, its associated techniques and technologies, and its increasing role in food science and research. The review provides a critical comparison and synthesis of tentative identification guidelines proposed for over 15 years, offering a condensed resource for researchers in the field. We have also examined a wide range of recent metabolomics studies, showcasing various methodologies and highlighting key findings as a testimony of the versatility of the field and the possibilities it offers. In doing so, we have also carefully provided a compilation of the software tools that may be employed in this type of studies. The manuscript also explores the prospects of high-resolution mass spectrometry and metabolomics in food science. By covering the history, guidelines, applications, and tools of metabolomics, this review attempts to become a comprehensive guide for researchers in a rapidly evolving field.

Integrated transcriptomics and metabolomics reveal specific phenolic and flavonoid accumulation in licorice (Glycyrrhiza uralensis Fisch.) induced by arbuscular mycorrhiza symbiosis under drought stress

Arbuscular mycorrhizal (AM) symbiosis can strengthen plant defense against abiotic stress, such as drought, through multiple mechanisms; however, the specialized chemical defenses induced by AM symbiosis are largely unknown. In a pot experiment, licorice (Glycyrrhiza uralensis Fisch.) inoculated with and without arbuscular mycorrhizal fungus Rhizophagus irregularis Schenck & Smith were grown under well-watered or water deficit conditions. Transcriptomic and metabolomic analyses were combined to investigate licorice root specialized metabolism induced by AM symbiosis under drought stress. Results showed that mycorrhizal plants had few dead leaves, less biomass reduction, and less differentially expressed genes and metabolite features in response to drought compared with nonmycorrhizal plants. Transcriptomic and metabolomic data revealed that mycorrhizal roots generally accumulated lignin regardless of the water regime; however, the expression of genes involved in lignin biosynthesis was significantly downregulated by drought stress in mycorrhizal plants. By contrast, AM inoculation significantly decreased specialized metabolites accumulation, including phenolics and flavonoids under well-watered conditions, whereas these decreases turned to be nonsignificant under drought stress. Moreover, these specific phenolics and flavonoids showed significant drought-induced accumulation pattern in mycorrhizal roots. These results highlight that accumulation of specific root phenolics and flavonoids may support the drought tolerance of mycorrhizal plants.

Influence of spontaneous, "pied de cuve" and commercial dry yeast fermentation strategies on wine molecular composition and sensory properties

While most producers in recent decades have relied on commercial yeasts (ADY) as their primary choice given their reliability and reproducibility, the fear of standardising the taste and properties of wine has led to the employment of alternative strategies that involve autochthonous yeasts such as pied de cuve (PdC) and spontaneous fermentation (SF). However, the impact of different fermentation strategies on wine has been a subject of debate and speculation. Consequently, this study describes, for the first time, the differences between the three kinds of fermentation at the metabolomic, chemical, and sensory levels in two wines: Chardonnay and Pinot Noir. The results showed how the yeast chosen significantly impacted the molecular composition of the wines, as revealed by metabolomic analysis that identified biomarkers with varying chemical compositions according to the fermentation modality. Notably, higher numbers of lipid markers were found for SF and PdC than ADY, which contained more peptides. Key molecules from the metabolic amino acid pathway, which are addressed in this article, showed evidence of such variations. In addition, the analysis of volatile aromatic compounds revealed an increase in groups of compounds specific to each fermentation. The sensorial analysis of Chardonnay wine showed a more qualitative sensory outcome (Higher fruit intensity) for ADY and SF compared to PdC. Our finding challenges the common speculation among wine producers that autochthonous yeast fermentations may offer greater complexity and uniqueness in comparison to commercial yeast fermentations.

Interplay of Metallome and Metabolome in Amyotrophic Lateral Sclerosis: A Study on Cerebrospinal Fluid of Patients Carrying Disease-Related Gene Mutations

Amyotrophic lateral sclerosis (ALS) is a lethal progressive neurodegenerative disease, characterized by a loss of function of upper and lower motor neurons. This study aimed to explore probable pathological alterations occurring in individuals with ALS compared to neurologically healthy controls through the analysis of cerebrospinal fluid (CSF), a medium, which directly interacts with brain parenchyma. A total of 7 ALS patients with disease-associated mutations (ATXN2, C9ORF72, FUS, SOD1, and TARDBP) and 13 controls were included in the study. Multiple analytical approaches were employed, including metabolomic and metallomics profiling, as well as genetic screening, using CSF samples obtained from the brain compartment. Data analysis involved the application of multivariate statistical methods. Advanced hyphenated selenium and redox metal (iron, copper, and manganese) speciation techniques and nontargeted Fourier transform ion cyclotron resonance mass spectrometry-based metabolomics were used for data acquisition. Nontargeted metabolomics showed reduced steroids, including sex hormones; additionally, copper and manganese species were found to be the most relevant features for ALS patients. This indicates a potential alteration of sex hormone pathways in the ALS-affected brain, as reflected in the CSF.

Untargeted Metabolomics Reveals Antidepressant Effects in a Marine Photosynthetic Organism: The Diatom Phaeodactylum tricornutum as a Case Study

The increased use of antidepressants, along with their increased occurrence in aquatic environments, is of concern for marine organisms. Although these pharmaceutical compounds have been shown to negatively affect marine diatoms, their mode of action in these non-target, single-cell phototrophic organisms is yet unknown. Using a Fourier-transform ion cyclotron-resonance mass spectrometer (FT-ICR-MS) we evaluated the effects of fluoxetine in the metabolomics of the model diatom Phaeodactylum tricornutum, as well as the potential use of the identified metabolites as exposure biomarkers. Diatom growth was severely impaired after fluoxetine exposure, particularly in the highest dose tested, along with a down-regulation of photosynthetic and carbohydrate metabolisms. Notably, several mechanisms that are normally down-regulated by fluoxetine in mammal organisms were also down-regulated in diatoms (e.g., glycerolipid metabolism, phosphatidylinositol signalling pathway, vitamin metabolism, terpenoid backbone biosynthesis and serotonin remobilization metabolism). Additionally, the present work also identified a set of potential biomarkers of fluoxetine exposure that were up-regulated with increasing fluoxetine exposure concentration and are of high metabolic significance following the disclosed mode of action, reinforcing the use of metabolomics approaches in ecotoxicology.

Microbiota independent effects of oligosaccharides on Caco-2 cells -A semi-targeted metabolomics approach using DI-FT-ICR-MS coupled with pathway enrichment analysis

Milk oligosaccharides (MOS) and galactooligosaccharides (GOS) are associated with many benefits, including anti-microbial effects and immune-modulating properties. However, the cellular mechanisms of these are largely unknown. In this study, the effects of enriched GOS and MOS mixtures from caprine and bovine milk consisting mainly 6'-galactosyllactose, 3'-sialyllactose, and 6'-sialyllactose on Caco-2 cells were investigated, and the treatment-specific metabolomes were described. In the control, the cells were treated with a sugar mix consisting of one-third each of glucose, galactose and lactose. A local metabolomics workflow with pathway enrichment was established, which specifically addresses DI-FT-ICR-MS analyses and includes adaptations in terms of measurement technology and sample matrices. By including quality parameters, especially the isotope pattern, we increased the precision of annotation. The independence from online tools, the fast adaptability to changes in databases, and the specific adjustment to the measurement technology and biomaterial used, proved to be a great advantage. For the first time it was possible to find 71 active pathways in a Caco-2 cell experiment. These pathways were assigned to 12 main categories, with amino acid metabolism and carbohydrate metabolism being the most dominant categories in terms of the number of metabolites and metabolic pathways. Treatment of Caco-2 cells with high GOS and glucose contents resulted in significant effects on several metabolic pathways, whereas the MOS containing treatments resulted only for individual metabolites in significant changes. An effect based on bovine or caprine origin alone could not be observed. Thus, it was shown that MOS and GOS containing treatments can exert microbiome-independent effects on the metabolome of Caco-2 cells.

Grapevine leaf MALDI-MS imaging reveals the localisation of a putatively identified sucrose metabolite associated to Plasmopara viticola development

Despite well-established pathways and metabolites involved in grapevine-Plasmopara viticola interaction, information on the molecules involved in the first moments of pathogen contact with the leaf surface and their specific location is still missing. To understand and localise these molecules, we analysed grapevine leaf discs infected with P. viticola with MSI. Plant material preparation was optimised, and different matrices and solvents were tested. Our data shows that trichomes hamper matrix deposition and the ion signal. Results show that putatively identified sucrose presents a higher accumulation and a non-homogeneous distribution in the infected leaf discs in comparison with the controls. This accumulation was mainly on the veins, leading to the hypothesis that sucrose metabolism is being manipulated by the development structures of P. viticola. Up to our knowledge this is the first time that the localisation of a putatively identified sucrose metabolite was shown to be associated to P. viticola infection sites.

An Open-Source Pipeline for Processing Direct Infusion Mass Spectrometry Data of the Human Plasma Metabolome

Direct infusion mass spectrometry (DIMS) is growing in popularity as an effective method for the screening of biological samples in clinical metabolomics. Being quick to execute, DIMS generally requires special skills when interpreting the results of measurements. By inspecting the similarities between two-dimensional electrospray ionization with quadrupole time-of-flight (ESI-QTOF) and matrix-assisted laser desorption/ionization (MALDI) mass spectra, the pipeline for processing QTOF mass spectra using open-source packages (MALDIquant, MSnbase and MetaboAnalystR) was tested. Previously, all algorithmic workflows have relied on the application of software either provided by a vendor or privately developed by enthusiasts. Here, we computationally examined two ways of interpreting the DIMS results of human blood metabolomic profiling. The studied spectra were acquired using ESI-QTOF maXis Impact II (Bruker Daltonics, Billerica, MA, USA), then pre-processed using COMPASS/DataAnalysis commercial software and mapped onto the metabolites using in-lab-developed MatLab scripts. Alternatively, in this work we used the open-source packages MALDIquant, for spectrum pre-processing, and MetaboAnalystR, for data interpretation, instead of the low-availability commercial and home-made tools. Using a set of 100 plasma samples (20 from volunteers with normal body mass index and 80 from patients at different stages of obesity), we observed a high degree of concordance in annotated metabolic pathways between the proprietary DataAnalysis/MatLab pipeline and our freely available solution.

Non-Targeted Metabolomics Approach Revealed Significant Changes in Metabolic Pathways in Patients with Chronic Traumatic Encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is frequently found in athletes and those who have experienced repetitive head traumas. CTE is associated with a variety of neuropathologies, which cause cognitive and behavioral impairments in CTE patients. However, currently, CTE can only be diagnosed after death via brain autopsy, and it is challenging to distinguish it from other neurodegenerative diseases with similar clinical features. To better understand this multifaceted disease and identify metabolic differences in the postmortem brain tissues of CTE patients and control subjects, we performed ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS)-based non-targeted metabolomics. Through multivariate and pathway analysis, we found that the brains of CTE patients had significant changes in the metabolites involved in astrocyte activation, phenylalanine, and tyrosine metabolism. The unique metabolic characteristics of CTE identified in this study were associated with cognitive dysfunction, amyloid-beta deposition, and neuroinflammation. Altogether, this study provided new insights into the pathogenesis of CTE and suggested appealing targets for both diagnosis and treatment for the disease.

Guide to Metabolomics Analysis: A Bioinformatics Workflow

Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach's ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.

Improved coverage of plant metabolites using powder laser desorption/ionization coupled with Fourier-transform ion cyclotron mass spectrometry

In this study, the effectiveness of powder laser desorption/ionization (LDI) coupled with Fourier-transform ion cyclotron mass spectrometry (FT-ICR MS) was evaluated for the improved coverage of plant metabolites. Ground plant (powder) was fixed on a metal plate using double-sided tape. Compared with the conventional approach involving liquid extraction, which is followed by electrospray ionization MS analysis, a smaller amount of sample (∼200 µg) was required in the proposed method. Additionally, the laborious steps of liquid extraction, concentration, and solid-phase extraction were avoided. Employing the proposed method in Centella asiatica leaves analysis, higher number of reproducible molecular formulas (>5000) and metabolites (>650) were obtained than the conventional methods. Flavonoids, phenolic acids, xanthones, lipids, carbohydrates, terpenoids, and alkaloids compounds were detected from leaves, stems, and roots of C. asiatica. This study indicates that LDI FT-ICR MS is a quick and effective tool for enhanced plant metabolite profiling in the solid phase.

Identification of Indicators for Preterm Birth Using Retinoid Metabolites

Metabolites reflect the biochemical dynamics for the maintenance of pregnancy and parturition. UPLC-Q/TOF-MS and LC-MS/MS metabolomics were performed to identify and validate the plasma metabolomic signatures of preterm birth (PTB). We recruited pregnant women between 16 and 40 weeks 5 days gestational age at Ewha Womans Mokdong Hospital for a nested case-control study. In untargeted UPLC-Q/TOF-MS, score plots of partial least-squares discriminant analysis clearly separated the PTB group from the term birth (TB, n = 10; PTB, n = 11). Fifteen metabolites were significantly different between the two groups, as indicated by a variable importance in projection >1 and p < 0.05. Metabolic pathways involving retinol, linoleic acid, d-arginine, and d-ornithine were associated with PTB. Verification by LC-MS/MS focused on retinol metabolism (TB, n = 39; PTB, n = 20). Retinol levels were significantly reduced in PTB compared to TB, while retinal palmitate, all-trans-retinal, and 13-cis-retinoic acid (¹³cis-RA) significantly increased (p < 0.05). Retinol-binding protein levels were also elevated in PTB. Additionally, all-trans-retinal (AUC 0.808, 95% CI: 0.683–0.933) and ¹³cis-RA (AUC 0.826, 95% CI: 0.723–0.930) showed improved predictions for PTB-related retinol metabolites. This study suggests that retinoid metabolism improves the accuracy of PTB predictions and plays an important role in maintaining pregnancy and inducing early parturition.

First screening of biocides, persistent organic pollutants, pharmaceutical and personal care products in Antarctic phytoplankton from Deception Island by FT-ICR-MS

In recent years, the Antarctic territory has seen a rise in the number of tourists and scientists. This has led to an increase in the anthropogenic footprint in Antarctic ecosystems, namely in terms of emerging contaminants, such as Biocides, Persistent Organic Pollutants (POPs) as well as Pharmaceutical and Personal Care Products (PPCPs). Yet scarce information on the presence of these emerging contaminants is available for trophic compartments, especially the phytoplankton community. Using high resolution Fourier-transform ion cyclotron-resonance mass spectrometry (FT-ICR-MS), an untargeted screening of the metabolome of the phytoplankton community was performed. Seventy different contaminant compounds were found to be present in phytoplankton collected at two sites in Port Foster Bay at Deception Island. These emerging contaminants included 1 polycyclic aromatic hydrocarbon (PAH), 10 biocides (acaricides, fungicides, herbicides, insecticides and nematicides), 11 POPs (flame retardants, paints and dyes, polychlorinated biphenyl (PCB), phthalates and plastic components), 5 PCPs (cosmetic, detergents and dietary compounds), 40 pharmaceutical compounds and 3 illicit drugs. Pharmaceutical compounds were, by far, the largest group of emerging contaminants found in phytoplankton cells (anticonvulsants, antihypertensives and beta-blockers, antibiotics, analgesic and anti-inflammatory drugs). The detection of several of these potentially toxic compounds at the basis of the marine food web has potentially severe impacts for the whole ecosystem trophic structure. Additionally, the present findings also point out that the guidelines proposed by the Antarctic Treaty and Protocol on Environmental Protection to the Antarctic Treaty should be revisited to avoid the proliferation of these and other PPCPs in such sensitive environments.

Enhanced Access to the Health-Related Skin Metabolome by Fast, Reproducible and Non-Invasive WET PREP Sampling

Our skin influences our physical and mental health, and its chemical composition can reflect environmental and disease conditions. Therefore, through sampling the skin metabolome, we can provide a promising window into the mechanisms of the body. However, the broad application of skin metabolomics has recently been hampered by a lack of easy and widely applicable sampling methods. Here, we present a novel rapid, simple, and, most importantly, painless and non-invasive sampling technique suitable for clinical studies of fragile or weakened skin. The method is called WET PREP and is simply a lavage of the skin which focuses on capturing the metabolome. We systematically evaluate WET PREPs in comparison with the non-invasive method of choice in skin metabolomics, swab collection, using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS²) on two complementary chromatographic columns (C18 reversed phase and hydrophilic interaction chromatography). We also integrate targeted analyses of key metabolites of skin relevance. Overall, WET PREP provides a strikingly more stable shared metabolome across sampled individuals, while also being able to capture unique individual metabolites with a high consistency in intra-individual reproducibility. With the exception of (phospho-)lipidomic studies, we recommend WET PREPs as the preferred skin metabolome sampling technique due to the quick preparation time, low cost, and gentleness for the patient.

Current and future deep learning algorithms for tandem mass spectrometry (MS/MS)-based small molecule structure elucidation

RATIONALE

Structure elucidation of small molecules has been one of the cornerstone applications of mass spectrometry for decades. Despite the increasing availability of software tools, structure elucidation from tandem mass spectrometry (MS/MS) data remains a challenging task, leaving many spectra unidentified. However, as an increasing number of reference MS/MS spectra are being curated at a repository scale and shared on public servers, there is an exciting opportunity to develop powerful new deep learning (DL) models for automated structure elucidation.

ARCHITECTURES

Recent early-stage DL frameworks mostly follow a "two-step approach" that translates MS/MS spectra to database structures after first predicting molecular descriptors. The related architectures could suffer from: (1) computational complexity because of the separate training of descriptor-specific classifiers, (2) the high dimensional nature of mass spectral data and information loss due to data preprocessing, (3) low substructure coverage and class imbalance problem of predefined molecular fingerprints. Inspired by successful DL frameworks employed in drug discovery fields, we have conceptualized and designed hypothetical DL architectures to tackle the above issues. For (1), we recommend multitask learning to achieve better performance with fewer classifiers by grouping structurally related descriptors. For (2) and (3), we introduce feature engineering to extract condensed and higher-order information from spectra and structure data. For instance, encoding spectra with subtrees and pre-calculated spectral patterns add peak interactions to the model input. Encoding structures with graph convolutional networks incorporates connectivity within a molecule. The joint embedding of spectra and structures can enable simultaneous spectral library and molecular database search.

CONCLUSIONS

In principle, given enough training data, adapted DL architectures, optimal hyperparameters and computing power, DL frameworks can predict small molecule structures, completely or at least partially, from MS/MS spectra. However, their performance and general applicability should be fairly evaluated against classical machine learning frameworks.

Metabolomics and transcriptomics to decipher molecular mechanisms underlying ectomycorrhizal root colonization of an oak tree

Mycorrhizas are known to have a positive impact on plant growth and ability to resist major biotic and abiotic stresses. However, the metabolic alterations underlying mycorrhizal symbiosis are still understudied. By using metabolomics and transcriptomics approaches, cork oak roots colonized by the ectomycorrhizal fungus Pisolithus tinctorius were compared with non-colonized roots. Results show that compounds putatively corresponding to carbohydrates, organic acids, tannins, long-chain fatty acids and monoacylglycerols, were depleted in ectomycorrhizal cork oak colonized roots. Conversely, non-proteogenic amino acids, such as gamma-aminobutyric acid (GABA), and several putative defense-related compounds, including oxylipin-family compounds, terpenoids and B6 vitamers were induced in mycorrhizal roots. Transcriptomic analysis suggests the involvement of GABA in ectomycorrhizal symbiosis through increased synthesis and inhibition of degradation in mycorrhizal roots. Results from this global metabolomics analysis suggest decreases in root metabolites which are common components of exudates, and in compounds related to root external protective layers which could facilitate plant-fungal contact and enhance symbiosis. Root metabolic pathways involved in defense against stress were induced in ectomycorrhizal roots that could be involved in a plant mechanism to avoid uncontrolled growth of the fungal symbiont in the root apoplast. Several of the identified symbiosis-specific metabolites, such as GABA, may help to understand how ectomycorrhizal fungi such as P. tinctorius benefit their host plants.

Soil assessment after chemical accidents using metabolic profiling and microbial community evaluation

This study investigated the effects of accidental contamination of soils with phenol, toluene, nitric acid, and hydrogen fluoride (HF) by simulating chemical leakage in the soil with/without rain and characterizing the resulting metabolites and microbial. In the case of acid leakage, pH and cation exchange capacity were decreased, and the content of fluoride ion was increased in case of HF leakage. Using mass spectrometry-based metabolomics analysis, phytosphingosine was detected as a distinguishing metabolite in soils contaminated with phenol and HF in rain conditions. Microbial communities were identified by 16s rRNA metagenome sequencing. Sphingomonas was one of the dominant species in soils contaminated with phenol and HF. These results suggest that phytosphingosine and Sphingomonas might be used as biomarkers to evaluate the status of soils contaminated with phenol or HF. Under simulated rain conditions, the species alpha-diversity index of soil microbes and the physicochemical properties of the soil indicated values close to those of the uncontaminated soil. Rain played an important role in the recovery of microbial and metabolic profiles after chemical accidents. Metabolic profiling and microbial community analysis can serve as a diagnostic tool for ecotoxicological research at chemical accident sites.

An apoplastic fluid extraction method for the characterization of grapevine leaves proteome and metabolome from a single sample

The analysis of complex biological systems keeps challenging researchers. The main goal of systems biology is to decipher interactions within cells, by integrating datasets from large scale analytical approaches including transcriptomics, proteomics and metabolomics and more specialized 'OMICS' such as epigenomics and lipidomics. Studying different cellular compartments allows a broader understanding of cell dynamics. Plant apoplast, the cellular compartment external to the plasma membrane including the cell wall, is particularly demanding to analyze. Despite our knowledge on apoplast involvement on several processes from cell growth to stress responses, its dynamics is still poorly known due to the lack of efficient extraction processes adequate to each plant system. Analyzing woody plants such as grapevine raises even more challenges. Grapevine is among the most important fruit crops worldwide and a wider characterization of its apoplast is essential for a deeper understanding of its physiology and cellular mechanisms. Here, we describe, for the first time, a vacuum-infiltration-centrifugation method that allows a simultaneous extraction of grapevine apoplastic proteins and metabolites from leaves on a single sample, compatible with high-throughput mass spectrometry analyses. The extracted apoplast from two grapevine cultivars, Vitis vinifera cv 'Trincadeira' and 'Regent', was directly used for proteomics and metabolomics analysis. The proteome was analyzed by nanoLC-MS/MS and more than 700 common proteins were identified, with highly diverse biological functions. The metabolome profile through FT-ICR-MS allowed the identification of 514 unique putative compounds revealing a broad spectrum of molecular classes.

Amplifying and Fine-Tuning Rsm sRNAs Expression and Stability to Optimize the Survival of Pseudomonas brassicacerum in Nutrient-Poor Environments

In the beneficial plant root-associated Pseudomonas brassicacearum strain NFM421, the GacS/GacA two-component system positively controls biofilm formation and the production of secondary metabolites through the synthesis of rsmX, rsmY and rsmZ. Here, we evidenced the genetic amplification of Rsm sRNAs by the discovery of a novel 110-nt long sRNA encoding gene, rsmX-2, generated by the duplication of rsmX-1 (formerly rsmX). Like the others rsm genes, its overexpression overrides the gacA mutation. We explored the expression and the stability of rsmX-1, rsmX-2, rsmY and rsmZ encoding genes under rich or nutrient-poor conditions, and showed that their amount is fine-tuned at the transcriptional and more interestingly at the post-transcriptional level. Unlike rsmY and rsmZ, we noticed that the expression of rsmX-1 and rsmX-2 genes was exclusively GacA-dependent. The highest expression level and longest half-life for each sRNA were correlated with the highest ppGpp and cyclic-di-GMP levels and were recorded under nutrient-poor conditions. Together, these data support the view that the Rsm system in P. brassicacearum is likely linked to the stringent response, and seems to be required for bacterial adaptation to nutritional stress.

Nanoemulsions of Satureja montana Essential Oil: Antimicrobial and Antibiofilm Activity against Avian Escherichia coli Strains

Satureja montana essential oil (SEO) presents a wide range of biological activities due to its high content of active phytochemicals. In order to improve the essential oil’s (EO) properties, oil in water nanoemulsions (NEs) composed of SEO and Tween-80 were prepared, characterized, and their antimicrobial and antibiofilm properties assayed against Escherichia coli strains isolated from healthy chicken. Since surfactant and oil composition can strongly influence NE features and their application field, a ternary phase diagram was constructed and evaluated to select a suitable surfactant/oil/water ratio. Minimal inhibitory concentration and minimal bactericidal concentration of NEs, evaluated by the microdilution method, showed that the SEO NE formulation exhibited higher inhibitory effects against planktonic E. coli than SEO alone. The quantification of biofilm production in the presence of NEs, assessed by crystal violet staining and scanning electron microscopy, evidenced that sub-MIC concentrations of SEO NEs enable an efficient reduction of biofilm production by the strong producer strains. The optimized nanoemulsion formulation could ensure food safety quality, and counteract the antibiotic resistance of poultry associated E. coli, if applied/aerosolized in poultry farms.

Seeing the forest for the trees: Retrieving plant secondary biochemical pathways from metabolome networks

Over the last decade, a giant leap forward has been made in resolving the main bottleneck in metabolomics, i.e., the structural characterization of the many unknowns. This has led to the next challenge in this research field: retrieving biochemical pathway information from the various types of networks that can be constructed from metabolome data. Searching putative biochemical pathways, referred to as biotransformation paths, is complicated because several flaws occur during the construction of metabolome networks. Multiple network analysis tools have been developed to deal with these flaws, while in silico retrosynthesis is appearing as an alternative approach. In this review, the different types of metabolome networks, their flaws, and the various tools to trace these biotransformation paths are discussed.

Metabolomic adjustments in the orchid mycorrhizal fungus Tulasnella calospora during symbiosis with Serapias vomeracea

All orchids rely on mycorrhizal fungi for organic carbon, at least during early development. In fact, orchid seed germination leads to the formation of a protocorm, a heterotrophic postembryonic structure colonized by intracellular fungal coils, thought to be the site of nutrient transfer. The molecular mechanisms underlying mycorrhizal interactions and metabolic changes induced by this symbiosis in both partners remain mostly unknown. We studied plant-fungus interactions in the mycorrhizal association between the Mediterranean orchid Serapias vomeracea and the basidiomycete Tulasnella calospora using nontargeted metabolomics. Plant and fungal metabolomes obtained from symbiotic structures were compared with those obtained under asymbiotic conditions. Symbiosis induced substantial metabolomic alterations in both partners. In particular, structural and signaling lipid compounds increased markedly in the external fungal mycelium growing near the symbiotic protocorms, whereas chito-oligosaccharides were identified uniquely in symbiotic protocorms. This work represents the first description of metabolic changes occurring in orchid mycorrhiza. These results - combined with previous transcriptomic data - provide novel insights on the mechanisms underlying the orchid mycorrhizal association and open intriguing questions on the role of fungal lipids in this symbiosis.

Water-Based Extraction of Bioactive Principles from Blackcurrant Leaves and Chrysanthellum americanum: A Comparative Study

The water-based extraction of bioactive components from flavonoid-rich medicinal plants is a key step that should be better investigated. This is especially true when dealing with easy-to-use home-made conditions of extractions, which are known to be a bottleneck in the course for a better control and optimization of the daily uptake of active components from medicinal plants. In this work, the water-based extraction of Blackcurrant (Ribes nigrum) leaves (BC) and Chrysanthellum americanum (CA), known to have complementary pharmacological properties, was studied and compared with a previous work performed on the extraction of Hawthorn (Crataegus, HAW). Various extraction modes in water (infusion, percolation, maceration, ultrasounds, microwaves) were compared for the extraction of bioactive principles contained in BC and CA in terms of extraction yield, of amount of flavonoids, phenolic compounds, and proanthocyanidin oligomers, and of UHPLC profiles of the extracted compounds. The qualitative and quantitative aspects of the extraction, in addition to the kinetic of extraction, were studied. The optimized easy-to-use-at-home extraction protocol developed for HAW was found very efficient to easily extract bioactive components from BC and CA plants. UHPLC-ESI-MS and high-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) were also implemented to get more qualitative information on the specific and common chemical compositions of the three plants (including HAW). Their antihyaluronidase, antioxidant, and antihypertensive activities were also determined and compared, demonstrating similar activities as the reference compound for some of these plants.

Integrating metabolomics and targeted gene expression to uncover potential biomarkers of fungal/oomycetes-associated disease susceptibility in grapevine

Vitis vinifera, one of the most cultivated fruit crops, is susceptible to several diseases particularly caused by fungus and oomycete pathogens. In contrast, other Vitis species (American, Asian) display different degrees of tolerance/resistance to these pathogens, being widely used in breeding programs to introgress resistance traits in elite V. vinifera cultivars. Secondary metabolites are important players in plant defence responses. Therefore, the characterization of the metabolic profiles associated with disease resistance and susceptibility traits in grapevine is a promising approach to identify trait-related biomarkers. In this work, the leaf metabolic composition of eleven Vitis genotypes was analysed using an untargeted metabolomics approach. A total of 190 putative metabolites were found to discriminate resistant/partial resistant from susceptible genotypes. The biological relevance of discriminative compounds was assessed by pathway analysis. Several compounds were selected as promising biomarkers and the expression of genes coding for enzymes associated with their metabolic pathways was analysed. Reference genes for these grapevine genotypes were established for normalisation of candidate gene expression. The leucoanthocyanidin reductase 2 gene (LAR2) presented a significant increase of expression in susceptible genotypes, in accordance with catechin accumulation in this analysis group. Up to our knowledge this is the first time that metabolic constitutive biomarkers are proposed, opening new insights into plant selection on breeding programs.

Dietary Intervention Reverses Fatty Liver and Altered Gut Microbiota during Early-Life Undernutrition

Nonalcoholic fatty liver disease (NAFLD), largely studied as a condition of overnutrition, also presents in undernourished populations. Like NAFLD, undernutrition disrupts systemic metabolism and has been linked to gut microbiota dysbiosis. Indeed, chronic exposures to fecal microbes contribute to undernutrition pathology in regions with poor sanitation. Despite a growing prevalence of fatty liver disease, the influence of undernutrition and the gut microbiota remain largely unexplored. Here, we utilize an established murine model (C57BL/6J mice placed on a malnourished diet that received iterative Escherichia coli/Bacteroidales gavage [MBG mice]) that combines a protein/fat-deficient diet and iterative exposure to specific, fecal microbes. Fecal-oral contamination exacerbates triglyceride accumulation in undernourished mice. MBG livers exhibit diffuse lipidosis accompanied by striking shifts in fatty acid, glycerophospholipid, and retinol metabolism. Multiomic analyses revealed metabolomic pathways linked to the undernourished gut microbiome and hepatic steatosis, including phenylacetate metabolism. Intriguingly, fatty liver features were observed only in the early-life, but not adult, MBG model despite similar liver metabolomic profiles. Importantly, we demonstrate that dietary intervention largely mitigates aberrant metabolomic and microbiome features in MBG mice. These findings indicate a crucial window in early-life development that, when disrupted by nutritional deficiency, may significantly influence liver function. Our work provides a multifaceted study of how diet and gut microbes inform fatty liver progression and reversal during undernutrition.IMPORTANCE Nonalcoholic fatty liver disease (NAFLD) remains a global epidemic, but it is often studied in the context of obesity and aging. Nutritional deficits, however, also trigger hepatic steatosis, influencing health trajectories in undernourished pediatric populations. Here, we report that exposure to specific gut microbes impacts fatty liver pathology in mice fed a protein/fat-deficient diet. We utilize a multiomics approach to (i) characterize NAFLD in the context of early undernutrition and (ii) examine the impact of diet and gut microbes in the pathology and reversal of hepatic steatosis. We provide compelling evidence that an early-life, critical development window facilitates undernutrition-induced fatty liver pathology. Moreover, we demonstrate that sustained dietary intervention largely reverses fatty liver features and microbiome shifts observed during early-life malnutrition.

Metabolomic and Signaling Programs Induced by Immobilized versus Soluble IFN γ in Neural Stem Cells

Neural stem cells (NSCs) provide a strategy to replace damaged neurons following traumatic central nervous system injuries. A major hurdle to translation of this therapy is that direct application of NSCs to CNS injury does not support sufficient neurogenesis due to lack of proper cues. To provide prolonged spatial cues to NSCs IFN-γ was immobilized to biomimetic hydrogel substrate to supply physical and biochemical signals to instruct the encapsulated NSCs to be neurogenic. However, the immobilization of factors, including IFN-γ, versus soluble delivery of the same factor, has been incompletely characterized especially with respect to activation of signaling and metabolism in cells over longer time points. In this study, protein and metabolite changes in NSCs induced by immobilized versus soluble IFN-γ at 7 days were evaluated. Soluble IFN-γ, refreshed daily over 7 days, elicited stronger responses in NSCs compared to immobilized IFN-γ, indicating that immobilization may not sustain signaling or has altered ligand/receptor interaction and integrity. However, both IFN-γ delivery types supported increased βIII tubulin expression in parallel with canonical and noncanonical receptor-signaling compared to no IFN-γ. Global metabolomics and pathway analysis revealed that soluble and immobilized IFN-γ altered metabolic pathway activities including energy, lipid, and amino acid synthesis, with soluble IFN-γ having the greatest metabolic impact overall. Finally, soluble and immobilized IFN-γ support mitochondrial voltage-dependent anion channel (VDAC) expression that correlates to differentiated NSCs. This work utilizes new methods to evaluate cell responses to protein delivery and provides insight into mode of action that can be harnessed to improve regenerative medicine-based strategies.

Decomposing the molecular complexity of brewing

The compositional space of a set of 120 diverse beer samples was profiled by rapid flow-injection analysis (FIA) Fourier transform ion cyclotron mass spectrometry (FTICR-MS). By the unrivaled mass resolution, it was possible to uncover and assign compositional information to thousands of yet unknown metabolites in the beer matrix. The application of several statistical models enabled the assignment of different molecular pattern to certain beer attributes such as the beer type, the way of adding hops and the grain used. The dedicated van Krevelen diagrams and mass difference networks displayed the structural connectivity of the annotated sum formulae. Thereby it was possible to provide a base of knowledge of the beer metabolome far above database-dependent annotations. Typical metabolic signatures for beer types, which reflect differences in ingredients and ways of brewing, could be extracted. Besides, the complexity of isomeric compounds, initially profiled as single mass values in fast FIA-FTICR-MS, was resolved by selective UHPLC-ToF-MS² analysis. Thereby structural hypotheses based on FTICR’s sum formulae could be confirmed. Benzoxazinoid hexosides deriving from the wheat’s secondary metabolism were uncovered as suitable marker substances for the use of whole wheat grains, in contrast to merely wheat starch or barley. Furthermore, it was possible to describe Hydroxymethoxybenzoxazinone(HMBOA)-hexosesulfate as a hitherto unknown phytoanticipin derivative in wheat containing beers. These findings raise the potential of ultrahigh resolution mass spectrometry for rapid quality control and inspection purposes as well as deep metabolic profiling, profound search for distinct hidden metabolites and classification of archeological beer samples.

Antioxidant activity from inactivated yeast: Expanding knowledge beyond the glutathione-related oxidative stability of wine

Maintaining wine oxidative stability during barrel ageing and shelf life storage remains a challenge. This study evaluated the antioxidant activities of soluble extracts from seven enological yeast derivatives (YDs) with increased glutathione (GSH) enrichment. YDs enriched in GSH appeared on average 3.3 times more efficient at quenching radical species than YDs not enriched in GSH. The lack of correlation (Spearman correlation ρ = 0.46) between the GSH concentration released from YDs and their radical scavenging activity shed light on other non-GSH compounds present. After 4-methyl-1,2-benzoquinone derivatization, UHPLC-Q-ToF MS analyses specifically identified 52 nucleophiles potentially representing an extensive molecular nucleophilic fingerprint of YDs. The comparative analysis of YD chemical oxidation conditions revealed that the nucleophilic molecular fingerprint of the YD was strongly correlated to its antiradical activity. The proposed strategy shows that nucleophiles co-accumulated with GSH during the enrichment of YDs are responsible for their antioxidant activities.

Advanced identification of global bioactivity hotspots via screening of the metabolic fingerprint of entire ecosystems

Natural products (NP) are a valuable drug resource. However, NP-inspired drug leads are declining, among other reasons due to high re-discovery rates. We developed a conceptual framework using the metabolic fingerprint of entire ecosystems (MeE) to facilitate the discovery of global bioactivity hotspots. We assessed the MeE of 305 sites of diverse aquatic ecosystems, worldwide. All samples were tested for antiviral effects against the human immunodeficiency virus (HIV), followed by a comprehensive screening for cell-modulatory activity by High-Content Screening (HCS). We discovered a very strong HIV-1 inhibition mainly in samples taken from fjords with a strong terrestrial input. Multivariate data integration demonstrated an association of a set of polyphenols with specific biological alterations (endoplasmic reticulum, lysosomes, and NFkB) caused by these samples. Moreover, we found strong HIV-1 inhibition in one unrelated oceanic sample closely matching to HIV-1-inhibitory drugs on a cytological and a chemical level. Taken together, we demonstrate that even without physical purification, a sophisticated strategy of differential filtering, correlation analysis, and multivariate statistics can be employed to guide chemical analysis, to improve de-replication, and to identify ecosystems with promising characteristics as sources for NP discovery.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

From genomics to metabolomics, moving toward an integrated strategy for the discovery of fungal secondary metabolites

Fungal secondary metabolites are defined by bioactive properties that ensure adaptation of the fungus to its environment. Although some of these natural products are promising sources of new lead compounds especially for the pharmaceutical industry, others pose risks to human and animal health. The identification of secondary metabolites is critical to assessing both the utility and risks of these compounds. Since fungi present biological specificities different from other microorganisms, this review covers the different strategies specifically used in fungal studies to perform this critical identification. Strategies focused on the direct detection of the secondary metabolites are firstly reported. Particularly, advances in high-throughput untargeted metabolomics have led to the generation of large datasets whose exploitation and interpretation generally require bioinformatics tools. Then, the genome-based methods used to study the entire fungal metabolic potential are reported. Transcriptomic and proteomic tools used in the discovery of fungal secondary metabolites are presented as links between genomic methods and metabolomic experiments. Finally, the influence of the culture environment on the synthesis of secondary metabolites by fungi is highlighted as a major factor to consider in research on fungal secondary metabolites. Through this review, we seek to emphasize that the discovery of natural products should integrate all of these valuable tools. Attention is also drawn to emerging technologies that will certainly revolutionize fungal research and to the use of computational tools that are necessary but whose results should be interpreted carefully.

Metabolomic Analysis Identifies Alterations of Amino Acid Metabolome Signatures in the Postmortem Brain of Alzheimer's Disease

Despite significant advances in neuroscience research over the past several decades, the exact cause of AD has not yet fully understood. The metabolic hypothesis as well as the amyloid and tau hypotheses have been proposed to be associated with AD pathogenesis. In order to identify metabolome signatures from the postmortem brains of sporadic AD patients and control subjects, we performed ultra performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometer (UPLC-LTQ-Orbitrap-MS). Not only our study identified new metabolome signatures but also verified previously known metabolome profiles in the brain. Statistical modeling of the analytical data and validation of the structural assignments discovered metabolic biomarkers associated with the AD pathogenesis. Interestingly, hypotaurin, myo-inositol and oxo-proline levels were markedly elevated in AD while lutamate and N-acetyl-aspartate were decreased in the postmortem brain tissue of AD patients. In addition, neurosteroid level such as cortisol was significantly increased in AD. Together, our data indicate that impaired amino acid metabolism is associated with AD pathogenesis and the altered amino acid signatures can be useful diagnostic biomarkers of AD. Thus, modulation of amino acid metabolism may be a possible therapeutic approach to treat AD.

Early stage metabolic events associated with the establishment of Vitis vinifera - Plasmopara viticola compatible interaction

Grapevine (Vitis vinifera L.) is the most widely cultivated and economically important fruit crop in the world, with 7.5 million of production area in 2017. The domesticated varieties of grapevine are highly susceptible to many fungal infections, of which downy mildew, caused by the biotrophic oomycete Plasmopara viticola (Berk. et Curt.) Berl. et de Toni is one of the most threatening. In V. vinifera, several studies have shown that a weak and transient activation of a defense mechanism occurs, but it is easily overcome by the pathogen leading to the establishment of a compatible interaction. Major transcript, protein and physiologic changes were shown to occur at later infection time-points, but comprehensive data on the first hours of interaction is scarce. In the present work, we investigated the major physiologic and metabolic changes that occur in the first 24 h of interaction between V. vinifera cultivar Trincadeira and P. viticola. Our results show that there was a negative modulation of several metabolic classes associated to pathogen defense such as flavonoids or phenylpropanoids as well as an alteration of carbohydrate content after inoculation with the pathogen. We also found an accumulation of hydrogen peroxide and increase of lipid peroxidation but to a low extent, that seems to be insufficient to restrain pathogen growth during the initial biotrophic phase of the interaction.

Mass Spectrometry-Based Profiling of Metabolites in Human Biofluids

Cancer poses a daunting challenge to researchers and clinicians alike. Early diagnosis, accurate prognosis, and prediction of therapeutic response remain elusive in most types of cancer. In addition, lacunae in our understanding of cancer biology continue to hinder advancement of therapeutic strategies. Metabolic reprogramming has been identified as integral to pathogenesis and progression of the disease. Consequently, analysis of biofluid metabolome has emerged as a promising approach to further our understanding of disease biology as well as to identify cancer biomarkers. However, unbiased identification of robust and meaningful differences in metabolic signatures remains a non-trivial task. This chapter describes a generalized strategy for global metabolic profiling of human biofluids using ultra-performance liquid chromatography (UPLC) and mass spectrometry, which together offer a sensitive, high-throughput, and versatile platform. A step-by-step protocol for performing untargeted metabolic profiling of urine and serum (or plasma), using hydrophilic interaction liquid chromatography (HILIC) or reverse-phase (RP) chromatography coupled with electrospray ionization mass spectrometry (ESI-MS) to multivariate data analysis and identification of metabolites of interest has been detailed.

Metabolomic investigations in cerebrospinal fluid of Parkinson's disease

The underlying mechanisms of Parkinson´s disease are not completely revealed. Especially, early diagnostic biomarkers are lacking. To characterize early pathophysiological events, research is focusing on metabolomics. In this case-control study we investigated the metabolic profile of 31 Parkinson´s disease-patients in comparison to 95 neurologically healthy controls. The investigation of metabolites in CSF was performed by a 12 Tesla SolariX Fourier transform-ion cyclotron resonance-mass spectrometer (FT-ICR-MS). Multivariate statistical analysis sorted the most important biomarkers in relation to their ability to differentiate Parkinson versus control. The affected metabolites, their connection and their conversion pathways are described by means of network analysis. The metabolic profiling by FT-ICR-MS in CSF yielded in a good group separation, giving insights into the disease mechanisms. A total number of 243 metabolites showed an affected intensity in Parkinson´s disease, whereas 15 of these metabolites seem to be the main biological contributors. The network analysis showed a connection to the tricarboxylic cycle (TCA cycle) and therefore to mitochondrial dysfunction and increased oxidative stress within mitochondria. The metabolomic analysis of CSF in Parkinson´s disease showed an association to pathways which are involved in lipid/ fatty acid metabolism, energy metabolism, glutathione metabolism and mitochondrial dysfunction.

Metabotype variation in a field population of tansy plants influences aphid host selection

It is well known that plant volatiles influence herbivores in their selection of a host plant; however, less is known about how the nonvolatile metabolome affects herbivore host selection. Metabolic diversity between intraspecific plants can be characterized using non-targeted mass spectrometry that gives us a snapshot overview of all metabolic processes occurring within a plant at a particular time. Here, we show that non-targeted metabolomics can be used to reveal links between intraspecific chemical diversity and ecological processes in tansy (Tanacetum vulgare). First, we show that tansy plants can be categorized into five subgroups based up on their metabolic profiles, and that these "metabotypes" influenced natural aphid colonization in the field. Second, this grouping was not due to induced metabolomic changes within the plant due to aphid feeding but rather resulted from constitutive differences in chemical diversity between plants. These findings highlight the importance of intraspecific chemical diversity within one plant population and provide the first report of a non-targeted metabolomic field study in chemical ecology.

The marine bacterium Phaeobacter inhibens secures external ammonium by rapid buildup of intracellular nitrogen stocks

Reduced nitrogen species are key nutrients for biological productivity in the oceans. Ammonium is often present in low and growth-limiting concentrations, albeit peaks occur during collapse of algal blooms or via input from deep sea upwelling and riverine inflow. Autotrophic phytoplankton exploit ammonium peaks by storing nitrogen intracellularly. In contrast, the strategy of heterotrophic bacterioplankton to acquire ammonium is less well understood. This study revealed the marine bacterium Phaeobacter inhibens DSM 17395, a Roseobacter group member, to have already depleted the external ammonium when only ∼⅓ of the ultimately attained biomass is formed. This was paralleled by a three-fold increase in cellular nitrogen levels and rapid buildup of various nitrogen-containing intracellular metabolites (and enzymes for their biosynthesis) and biopolymers (DNA, RNA and proteins). Moreover, nitrogen-rich cells secreted potential RTX proteins and the antibiotic tropodithietic acid, perhaps to competitively secure pulses of external ammonium and to protect themselves from predation. This complex response may ensure growing cells and their descendants exclusive provision with internal nitrogen stocks. This nutritional strategy appears prevalent also in other roseobacters from distant geographical provenances and could provide a new perspective on the distribution of reduced nitrogen in marine environments, i.e. temporary accumulation in bacterioplankton cells.

PiMP my metabolome: an integrated, web-based tool for LC-MS metabolomics data

Summary

The Polyomics integrated Metabolomics Pipeline (PiMP) fulfils an unmet need in metabolomics data analysis. PiMP offers automated and user-friendly analysis from mass spectrometry data acquisition to biological interpretation. Our key innovations are the Summary Page, which provides a simple overview of the experiment in the format of a scientific paper, containing the key findings of the experiment along with associated metadata; and the Metabolite Page, which provides a list of each metabolite accompanied by ‘evidence cards’, which provide a variety of criteria behind metabolite annotation including peak shapes, intensities in different sample groups and database information.

Availability and implementation

PiMP is available at http://polyomics.mvls.gla.ac.uk, and access is freely available on request. 50 GB of space is allocated for data storage, with unrestricted number of samples and analyses per user. Source code is available at https://github.com/RonanDaly/pimp and licensed under the GPL.

Supplementary information

Supplementary data are available at Bioinformatics online.

Metabolomic insights into the effects of thyroid hormone on Rana [Lithobates] catesbeiana metamorphosis using whole-body Matrix Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging (MALDI-MSI)

Anuran metamorphosis involves the transformation of an aquatic tadpole into a juvenile frog. This process is completely dependent upon thyroid hormones (THs). Although much research has been focused on changes in gene expression programs during this postembryonic developmental period, transitions in the metabolic profiles are relatively poorly understood. Matrix Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging (MALDI-MSI) is a technique that generates highly multiplexed mass spectra while retaining spatial location information on a thin tissue section. Reconstructed ion heat maps are correlated with morphology of the tissue section for biological interpretation. The present study is the first to use whole-body MALDI-MSI on tadpoles to gain insights into anuran metamorphosis. Approximately 1000 features were detected in each of five tissues examined (brain, eye, liver, notochord, and tail muscle) from premetamorphic North American bullfrog (Rana [Lithobates] catesbeiana) tadpoles. Of these detected metabolites, 1700 were unique and 136 were significantly affected by exposure to 50 nM thyroxine for 48 h. Of the significantly-affected metabolites, 64 features were tentatively identified using the MassTRIX annotation tool. All tissues revealed changes in lipophilic compounds including phosphatidylcholines, phosphatidylinositols, phosphatidylglycerols, phosphatidylethanolamines, and phosphatidylserines. These lipophilic compounds made up the largest portion of significantly-affected metabolites indicating that lipid signaling is a major target of TH action in frog tadpoles.

Short-Term Exposure to Nitrogen Dioxide Provides Basal Pathogen Resistance

Nitrogen dioxide (NO2) forms in plants under stress conditions, but little is known about its physiological functions. Here, we explored the physiological functions of NO2 in plant cells using short-term fumigation of Arabidopsis (Arabidopsis thaliana) for 1 h with 10 µL L-1 NO2. Although leaf symptoms were absent, the expression of genes related to pathogen resistance was induced. Fumigated plants developed basal disease resistance, or pattern-triggered immunity, against the necrotrophic fungus Botrytis cinerea and the hemibiotrophic bacterium Pseudomonas syringae Functional salicylic acid and jasmonic acid (JA) signaling pathways were both required for the full expression of NO2-induced resistance against B. cinerea An early peak of salicylic acid accumulation immediately after NO2 exposure was followed by a transient accumulation of oxophytodienoic acid. The simultaneous NO2-induced expression of genes involved in jasmonate biosynthesis and jasmonate catabolism resulted in the complete suppression of JA and JA-isoleucine (JA-Ile) accumulation, which was accompanied by a rise in the levels of their catabolic intermediates 12-OH-JA, 12-OH-JA-Ile, and 12-COOH-JA-Ile. NO2-treated plants emitted the volatile monoterpene α-pinene and the sesquiterpene longifolene (syn. junipene), which could function in signaling or direct defense against pathogens. NO2-triggered B. cinerea resistance was dependent on enhanced early callose deposition and CYTOCHROME P450 79B2 (CYP79B2), CYP79B3, and PHYTOALEXIN DEFICIENT3 gene functions but independent of camalexin, CYP81F2, and 4-OH-indol-3-ylmethylglucosinolate derivatives. In sum, exogenous NO2 triggers basal pathogen resistance, pointing to a possible role for endogenous NO2 in defense signaling. Additionally, this study revealed the involvement of jasmonate catabolism and volatiles in pathogen immunity.

Arctic, Antarctic, and temperate green algae Zygnema spp. under UV-B stress: vegetative cells perform better than pre-akinetes

Species of Zygnema form macroscopically visible mats in polar and temperate terrestrial habitats, where they are exposed to environmental stresses. Three previously characterized isolates (Arctic Zygnema sp. B, Antarctic Zygnema sp. C, and temperate Zygnema sp. S) were tested for their tolerance to experimental UV radiation. Samples of young vegetative cells (1 month old) and pre-akinetes (6 months old) were exposed to photosynthetically active radiation (PAR, 400-700 nm, 400 μmol photons m^-2 s^-1) in combination with experimental UV-A (315-400 nm, 5.7 W m^-2, no UV-B), designated as PA, or UV-A (10.1 W m^-2) + UV-B (280-315 nm, 1.0 W m^-2), designated as PAB. The experimental period lasted for 74 h; the radiation period was 16 h PAR/UV-A per day, or with additional UV-B for 14 h per day. The effective quantum yield, generally lower in pre-akinetes, was mostly reduced during the UV treatment, and recovery was significantly higher in young vegetative cells vs. pre-akinetes during the experiment. Analysis of the deepoxidation state of the xanthophyll-cycle pigments revealed a statistically significant (p < 0.05) increase in Zygnema spp. C and S. The content of UV-absorbing phenolic compounds was significantly higher (p < 0.05) in young vegetative cells compared to pre-akinetes. In young vegetative Zygnema sp. S, these phenolic compounds significantly increased (p < 0.05) upon PA and PAB. Transmission electron microscopy showed an intact ultrastructure with massive starch accumulations at the pyrenoids under PA and PAB. A possible increase in electron-dense bodies in PAB-treated cells and the occurrence of cubic membranes in the chloroplasts are likely protection strategies. Metabolite profiling by non-targeted RP-UHPLC-qToF-MS allowed a clear separation of the strains, but could not detect changes due to the PA and PAB treatments. Six hundred seventeen distinct molecular masses were detected, of which around 200 could be annotated from databases. These results indicate that young vegetative cells can adapt better to the experimental UV-B stress than pre-akinetes.

Identification of redox imbalance as a prominent metabolic response elicited by rapeseed feeding in swine metabolome

Rapeseed (RS) is an abundant and inexpensive source of energy and AA in diets for monogastrics and a sustainable alternative to soybean meal. It also contains diverse bioactive phytochemicals that could have antinutritional effects at high dose. When the RS-derived feed ingredients (RSF) are used in swine diets, the uptake of these nutrients and phytochemicals is expected to affect the metabolic system. In this study, 2 groups of young pigs (17.8 ± 2.7 kg initial BW) were equally fed a soybean meal-based control diet and an RSF-based diet, respectively, for 3 wk. Digesta, liver, and serum samples from these pigs were examined by liquid chromatography-mass spectrometry-based metabolomic analysis to determine the metabolic effects of the 2 diets. Analyses of digesta samples revealed that sinapine, sinapic acid, and gluconapin were robust exposure markers of RS. The distribution of free AA along the intestine of RSF pigs was consistent with the reduced apparent ileal digestibility of AA observed in these pigs. Despite its higher fiber content, the RSF diet did not affect microbial metabolites in the digesta, including short-chain fatty acids and secondary bile acids. Analyses of the liver and serum samples revealed that RSF altered the levels of AA metabolites involved in the urea cycle and 1-carbon metabolism. More importantly, RSF increased the levels of multiple oxidized metabolites and aldehydes while decreased the levels of ascorbic acid and docosahexaenoic acid-containing lipids in the liver and serum, suggesting that RSF could disrupt redox balance in young pigs. Overall, the results indicated that RSF elicited diverse metabolic events in young pigs through its influences on nutrient and antioxidant metabolism, which might affect the performance and health in long-term feeding and also provide the venues for nutritional and processing interventions to improve the utilization of RSF in pigs.

Identification of activation of tryptophan-NAD+ pathway as a prominent metabolic response to thermally oxidized oil through metabolomics-guided biochemical analysis

Consumption of thermally oxidized oil is associated with metabolic disorders, but oxidized oil-elicited changes in the metabolome are not well defined. In this study, C57BL/6 mice were fed the diets containing either control soybean oil or heated soybean oil (HSO) for 4 weeks. HSO-responsive metabolic events were examined through untargeted metabolomics-guided biochemical analysis. HSO directly contributed to the presence of new HSO-derived metabolites in urine and the decrease of polyunsaturated fatty acid-containing phospholipids in serum and the liver. HSO disrupted redox balance by decreasing hepatic glutathione and ascorbic acid. HSO also activated peroxisome proliferator-activated receptors, leading to the decrease of serum triacylglycerols and the changes of cofactors and products in fatty acid oxidation pathways. Most importantly, multiple metabolic changes, including the decrease of tryptophan in serum; the increase of NAD⁺ in the liver; the increases of kynurenic acid, nicotinamide and nicotinamide N-oxide in urine; and the decreases of the metabolites from pyridine nucleotide degradation in the liver indicated that HSO activated tryptophan-NAD⁺ metabolic pathway, which was further confirmed by the upregulation of gene expression in this pathway. Because NAD⁺ and its metabolites are essential cofactors in many HSO-induced metabolic events, the activation of tryptophan-NAD⁺ pathway should be considered as a central metabolic response to the exposure of HSO.

Mycorrhiza-Triggered Transcriptomic and Metabolomic Networks Impinge on Herbivore Fitness

Symbioses between plants and mycorrhizal fungi are ubiquitous in ecosystems and strengthen the plants' defense against aboveground herbivores. Here, we studied the underlying regulatory networks and biochemical mechanisms in leaves induced by ectomycorrhizae that modify herbivore interactions. Feeding damage and oviposition by the widespread poplar leaf beetle Chrysomela populi were reduced on the ectomycorrhizal hybrid poplar Populus × canescens Integration of transcriptomics, metabolomics, and volatile emission patterns via mass difference networks demonstrated changes in nitrogen allocation in the leaves of mycorrhizal poplars, down-regulation of phenolic pathways, and up-regulation of defensive systems, including protease inhibitors, chitinases, and aldoxime biosynthesis. Ectomycorrhizae had a systemic influence on jasmonate-related signaling transcripts. Our results suggest that ectomycorrhizae prime wounding responses and shift resources from constitutive phenol-based to specialized protective compounds. Consequently, symbiosis with ectomycorrhizal fungi enabled poplars to respond to leaf beetle feeding with a more effective arsenal of defense mechanisms compared with nonmycorrhizal poplars, thus demonstrating the importance of belowground plant-microbe associations in mitigating aboveground biotic stress.

From correlation to causation: analysis of metabolomics data using systems biology approaches

INTRODUCTION

Metabolomics is a well-established tool in systems biology, especially in the top-down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

OBJECTIVES

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

METHODS

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

RESULTS

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

CONCLUSIONS

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data

BACKGROUND

Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined.

RESULTS

An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites.

CONCLUSIONS

We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration

Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCoreTM, MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration.

Randomized controlled trial on the impact of early-life intervention with bifidobacteria on the healthy infant fecal microbiota and metabolome

Background: Early-life colonization of the intestinal tract is a dynamic process influenced by numerous factors. The impact of probiotic-supplemented infant formula on the composition and function of the infant gut microbiota is not well defined.Objective: We sought to determine the effects of a bifidobacteria-containing formula on the healthy human intestinal microbiome during the first year of life.Design: A double-blind, randomized, placebo-controlled study of newborn infants assigned to a standard whey-based formula containing a total of 10⁷ colony-forming units (CFU)/g of Bifidobacterium bifidum, Bifidobacterium breve, Bifidobacterium longum, B. longum subspecies infantis (intervention), or to a control formula without bifidobacteria (placebo). Breastfed controls were included. Diversity and composition of fecal microbiota were determined by 16S ribosomal RNA gene amplicon sequencing, and metabolite profiles were analyzed by ultrahigh-performance liquid chromatography-mass spectrometry over a period of 2 y.Results: Infants (n = 106) were randomly assigned to either the interventional (n = 48) or placebo (n = 49) group; 9 infants were exclusively breastfed throughout the entire intervention period of 12 mo. Infants exposed to bifidobacteria-supplemented formula showed decreased occurrence of Bacteroides and Blautia spp. associated with changes in lipids and unknown metabolites at month 1. Microbiota and metabolite profiles of intervention and placebo groups converged during the study period, and long-term colonization (24 mo) of the supplemented Bifidobacterium strains was not detected. Significant differences in microbiota and metabolites were detected between infants fed breast milk and those fed formula (P < 0.005) and between infants birthed vaginally and those birthed by cesarean delivery (P < 0.005). No significant differences were observed between infant feeding groups regarding growth, antibiotic uptake, or other health variables (P > 0.05).Conclusion: The supplementation of bifidobacteria to infant diet can modulate the occurrence of specific bacteria and metabolites during early life with no detectable long-term effects. This trial was registered at germanctr.de as DRKS00003660.