Metabolomic Tools Research Articles

Metabolomics-Based Evaluation of Crop Quality Changes as a Consequence of Climate Change.

Fruit composition determines the fruit quality and, consequently, consumer acceptance. As fruit quality can be modified by environmental conditions, it will be impacted by future alterations produced by global warming. Therefore, agricultural activities will be influenced by the changes in climatological conditions in cultivable areas, which could have a high socioeconomic impact if fruit production and quality decline. Currently, different stresses are being applied to several cultivated species to evaluate their impact on fruit metabolism and plant performance. With the use of metabolomic tools, these changes can be precisely measured, allowing us to determine changes in the patterns of individual compounds. As these changes depend on both the stress severity and the specific species involved and even on the specific cultivar, individual analysis must be conducted. To date, the most-studied crops have mainly been crops that are widely cultivated and have a high socioeconomic impact. In the near future, with the development of these metabolomic strategies, their implementation will be extended to other species, which will allow the adaptation of cultivation conditions and the development of varieties with high adaptability to climatological changes.

Disease Differentiation and Monitoring of Anti-TNF Treatment in Rheumatoid Arthritis and Spondyloarthropathies.

Rheumatoid arthritis (RA), ankylosing spondylitis (AS), and psoriatic arthritis (PsA) are comprehensive immunological disorders. The treatment of these disorders is limited to ameliorating the symptoms and improving the quality of life of patients. In this study, serum samples from RA, AS, and PsA patients were analyzed with metabolomic tools employing the 1H NMR method in combination with univariate and multivariate analyses. The results obtained in this study showed that the changes in metabolites were the highest for AS > RA > PsA. The study demonstrated that the time until remission or until low disease activity is achieved is shortest (approximately three months) for AS, longer for RA and longest for PsA. The statistically common metabolite that was found to be negatively correlated with the healing processes of these disorders is ethanol, which may indicate the involvement of the gut microflora and/or the breakdown of malondialdehyde as a cell membrane lipid peroxide product.

Identification of Key Metabolic Pathways and Biomarkers Underlying Flowering Time of Guar (Cyamopsis tetragonoloba (L.) Taub.) via Integrated Transcriptome-Metabolome Analysis.

Guar (Cyamopsis tetragonoloba (L.) Taub.) is an annual legume crop native to India and Pakistan. Seeds of the plant serve as a source of galactomannan polysaccharide (guar gum) used in the food industry as a stabilizer (E412) and as a gelling agent in oil and gas fracturing fluids. There were several attempts to introduce this crop to countries of more northern latitudes. However, guar is a plant of a short photoperiod, therefore, its introduction, for example, to Russia is complicated by a long day length during the growing season. Breeding of new guar varieties insensitive to photoperiod slowed down due to the lack of information on functional molecular markers, which, in turn, requires information on guar genome. Modern breeding strategies, e.g., genomic predictions, benefit from integration of multi-omics approaches such as transcriptome, proteome and metabolome assays. Here we present an attempt to use transcriptome-metabolome integration to understand the genetic determination of flowering time variation among guar plants that differ in their photoperiod sensitivity. This study was performed on nine early- and six delayed-flowering guar varieties with the goal to find a connection between 63 metabolites and 1,067 differentially expressed transcripts using Shiny GAM approach. For the key biomarker of flowering in guar myo-inositol we also evaluated the KEGG biochemical pathway maps available for Arabidopsis thaliana. We found that the phosphatidylinositol signaling pathway is initiated in guar plants that are ready for flowering through the activation of the phospholipase C (PLC) gene, resulting in an exponential increase in the amount of myo-inositol in its free form observed on GC-MS chromatograms. The signaling pathway is performed by suppression of myo-inositol phosphate kinases (phosphorylation) and alternative overexpression of phosphatases (dephosphorylation). Our study suggests that metabolome and transcriptome information taken together, provide valuable information about biomarkers that can be used as a tool for marker-assisted breeding, metabolomics and functional genomics of this important legume crop.

HGG-44. REVEALING VULNERABILITIES IN DIPG THROUGH ONC201

Emerging evidence from clinical and preclinical studies suggests that the imipridone ONC201 is well tolerated and may have some clinical impact in discrete diffuse intrinsic pontine glioma patients (DIPG). A primary goal of our work is to determine if DIPG are uniquely sensitive to ONC201 and if so, whether ONC201 itself can be used as a tool to illuminate novel vulnerabilities in DIPG. To accomplish this, we are utilizing a combination of patient-derived cell lines as well as mouse xenografts that dovetail with a variety of molecular, epigenetic and metabolomic tools. A central finding from our work is that ONC201 primarily activates the mitochondrial protease, ClpP in DIPG patient-derived cell lines, an effect consistent with recently described ONC201 mechanism of action in other tumors. We further demonstrate that activation of ClpP by ONC201 leads to a host of downstream effects in DIPG model systems including distinctive effects on the metabolome leading to direct alterations in the unique epigenetic signature of DIPG. By directly manipulating these metabolic and epigenetic factors we provide prospective mechanistic insight into how ONC201 as well as ClpP activity impacts DIPG growth and tumorigenicity. These preclinical research findings shed light on potential therapeutic vulnerabilities in DIPG as well as ways that these strategies may be combined to enhance their potential.

MS2Compound: A User-Friendly Compound Identification Tool for LC-MS/MS-Based Metabolomics Data.

Metabolomics is a leading frontier of systems science and biomedical innovation. However, metabolite identification in mass spectrometry (MS)-based global metabolomics investigations remains a formidable challenge. Moreover, lack of comprehensive spectral databases hinders accurate identification of compounds in global MS-based metabolomics. Creating experiment-derived metabolite spectral libraries tailored to each experiment is labor-intensive. Therefore, predicted spectral libraries could serve as a better alternative. User-friendly tools are much needed, as the currently available metabolomic analysis tools do not offer adequate provision for users to create or choose context-specific databases. Here, we introduce the MS2Compound, a metabolite identification tool, which can be used to generate a custom database of predicted spectra using the Competitive Fragmentation Modeling-ID (CFM-ID) algorithm, and identify metabolites or compounds from the generated database. The database generator can create databases of the model/context/species used in the metabolomics study. The MS2Compound is also powered with mS-score, a scoring function for matching raw fragment spectra to a predicted spectra database. We demonstrated that mS-score is robust in par with dot product and hypergeometric score in identifying metabolites using benchmarking datasets. We evaluated and highlight here the unique features of the MS2Compound by a re-analysis of a publicly available metabolomic dataset (MassIVE id: MSV000086784) for a complex traditional drug formulation called Triphala. In conclusion, we believe that the omics systems science and biomedical research and innovation community in the field of metabolomics will find the MS2Compound as a user-friendly analysis tool of choice to accelerate future metabolomic analyses.

Pushing the Proteomics Envelope: More sensitive technology spurs proteomic and metabolomic biomarker identification, clinical use

Pushing the Proteomics Envelope: More sensitive technology spurs proteomic and metabolomic biomarker identification, clinical use

New software tools, databases, and resources in metabolomics: updates from 2020.

BackgroundPrecision medicine, space exploration, drug discovery to characterization of dark chemical space of habitats and organisms, metabolomics takes a centre stage in providing answers to diverse biological, biomedical, and environmental questions. With technological advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of analytical instrumentation. Software tools, resources, databases, and solutions help in harnessing the concealed information in the generated data for eventual translational success.Aim of the reviewIn this review, ~ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community.Key scientific concepts of reviewIn Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.

Sponge-associated sp. RM66 metabolome induction with N-acetylglucosamine: Antibacterial, antifungal and anti-trypanosomal activities.

The marine sponge Amphimedon sp., collected from Hurghada (Egypt) was investigated for its sponge-derived actinomycetes diversity. Nineteen actinomycetes were cultivated and phylogenetically identified using 16S rDNA gene sequencing were carried out. The strains belong to genera Kocuria, Dietzia, Micrococcus, Microbacterium and Streptomyces. Many silent biosynthetic genes clusters were investigated using genome sequencing of actinomycete strains and has revealed in particular the genus Streptomyces that has indicated their exceptional capacity for the secondary metabolites production that not observed under classical cultivation conditions. In this study, the effect of N-acetylglucosamine on the metabolome of Streptomyces sp. RM66 was investigated using three actinomycetes media (ISP2, M1 and MA). In total, twelve extracts were produced using solid and liquid fermentation approaches. Liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) data were analysed using metabolomics tools to compare natural product production across all crude extracts. Our study highlighted the elicitation effect of N-acetylglucosamine on the secondary metabolite profiles of Streptomyces sp. RM66. These results highlight the of N-acetylglucosamine application as an elicitor to induce the cryptic metabolites and for increasing the chemical diversity. All the twelve extracts were tested for their antibacterial activity was tested against Staphylococcus aureus NCTC 8325, antifungal activity against Candida albicans 5314 (ATCC 90028) and anti-trypanosomal activity against Trypanosoma brucei brucei. Extract St1 showed the most potent one with activities 2.3, 3.2 and 4.7 ug/ml as antibacterial, antifungal and anti-trypanosomal, respectively.

Risk management of infectious disease using multidimensional Omics: Molecular diagnostic and personal care of tuberculosis

Tuberculosis (TB) is one of the top 10 leading causes of death worldwide responsible for over 1.5 million deaths annually. It is caused by hazardous biological pathogen (i.e., Mycobacterium tuberculosis (MTB)) with single infectious agent, surpassing even HIV/AIDS. Roughly one-quarter of the world's population has latent TB, meaning that people have been infected by tuberculosis bacteria but have not yet developed the disease. Patients with active tuberculosis on average infect five to fifteen other people via airborne droplets. Once infected, people with HIV are 19 times more likely to develop active tuberculosis which has almost 100% mortality for this group, if not treated properly. Comparatively, 45% of HIV negative people will die if they develop active tuberculosis and are not adequately medicated. This is concerning since 95% of cases and deaths are in developing countries, where treatments and diagnosis may not be timely. Additionally, current detection methods do not distinguish active tuberculosis from a cleared or latent infection while microbiological culture of mycobacteria is slow. However, medical discoveries and newly developed technologies allowed for unification of disciplines incorporating omics into everyday biological research. The goal of this short review is to demonstrate ways in which field of multidimensional Omics could contributed to the advanced detection of infectious disease by improving accuracy and quality of patient care by implementing molecular based detection of pathogen (i.e., antigenicity and metabolomics tools) as well as personal care with follow-up monitoring care (i.e., immunogenicity and vaccinomics tools) in the diagnosis, treatment, and prevention of tuberculosis.

Characterization of the Exo-Metabolome of the Emergent Phytopathogen Fusarium kuroshium sp. nov., a Causal Agent of Fusarium Dieback.

Fusarium kuroshium is the fungal symbiont associated with the ambrosia beetle Euwallacea kuroshio, a plague complex that attacks avocado, among other hosts, causing a disease named Fusarium dieback (FD). However, the contribution of F. kuroshium to the establishment of this disease remains unknown. To advance the understanding of F. kuroshium pathogenicity, we profiled its exo-metabolome through metabolomics tools based on accurate mass spectrometry. We found that F. kuroshium can produce several key metabolites with phytotoxicity properties and other compounds with unknown functions. Among the metabolites identified in the fungal exo-metabolome, fusaric acid (FA) was further studied due to its phytotoxicity and relevance as a virulence factor. We tested both FA and organic extracts from F. kuroshium at various dilutions in avocado foliar tissue and found that they caused necrosis and chlorosis, resembling symptoms similar to those observed in FD. This study reports for first-time insights regarding F. kuroshium associated with its virulence, which could lead to the potential development of diagnostic and management tools of FD disease and provides a basis for understanding the interaction of F. kuroshium with its host plants.

Understanding the Interactions between Staphylococcus aureus and the Raw-Meat-Processing Environment Isolate Klebsiella oxytoca in Dual-Species Biofilms via Discovering an Altered Metabolic Profile.

In a raw-meat-processing environment, members of the Enterobacteriaceae family can coexist with Staphylococcus aureus to form dual-species biofilms, leading to a higher risk of food contamination. However, very little is known about the effect of inter-species interactions on dual-species biofilm formation. The aim of this study was to investigate the interactions between S. aureus and raw-meat-processing environment isolates of Klebsiella oxytoca in dual-species biofilms, by employing an untargeted metabolomics tool. Crystal violet staining assay showed that the biomass of the dual-species biofilm significantly increased and reached its maximum after incubation for 21 h, compared with that of single species grown alone. The number of K. oxytoca in the dual-species biofilm was significantly higher than that of S. aureus. Field emission scanning electron microscopy (FESEM) revealed that both species were evenly distributed, and were tightly wrapped by extracellular polymeric substances in the dual-species biofilms. Ultra-high-pressure liquid chromatography equipped with a quadrupole-time-of-flight mass spectrometer (UHPLC-Q-TOF MS) analysis exhibited a total of 8184 positive ions, and 6294 negative ions were obtained from all test samples. Multivariate data analysis further described altered metabolic profiling between mono- and dual-species biofilms. Further, 18 and 21 different metabolites in the dual-species biofilm were screened as biomarkers by comparing the mono-species biofilms of S. aureus and K. oxytoca, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were exclusively upregulated in the dual-species biofilm included ABC transporters, amino acid metabolism, and the two-component signal transduction system. Our results contribute to a better understanding of the interactive behavior of inter-species biofilm communities, by discovering altered metabolic profiling.

The antimicrobial peptide AsR416 can inhibit the growth, sclerotium formation and virulence of Rhizoctonia solani AG1-IA

Plant antimicrobial peptides (AMPs) as a part of plant defense responses, are small soluble defense molecules which can inhibit the growth of pathogens. This study evaluates the effect of an antimicrobial peptide obtained from Allium sativum (AsR416) on Rhizoctonia solani (AG1-IA) the causal agent of rice sheath blight, in vitro and in vivo conditions. Firstly, the obtained results revealed that AsR416 (100 mg ml−1) inhibited the growth and sclerotia production of R. solani AG1-IA. Furthermore, these results showed the mode of action and mechanisms of AsR416 effect in inhibiting sclerotia formation of R. solani AG1-IA via metabolomics tools. AsR416 decreased the biomass of R. solani AG1-IA in liquid culture. In addition, nitro blue tetrazolium and evans blue staining methods revealed that the antimicrobial peptide induced O2− formation in the hyphal cells and mycelia cell death of R. solani AG1-IA, respectively. AsR416 delayed the pathogen infection process and decreased the severity of rice sheath blight disease in vitro and in vivo conditions. AsR416 reduced activity of cellulase, which is one of the virulence factors of this pathogen. The number of sclerotia decreased on plants treated with AsR416 after 2 months compared with the control. Considering the need to reduce application of hazardous synthetic fungicides against pathogenic fungi, using AMPs could be a successful method to increase rice production and reduce the use of chemical fungicides against sheath blight disease.

Benchmarking Non-Targeted Metabolomics Using Yeast-Derived Libraries.

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at −80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

Metabolomics: A Powerful Tool to Study the Complexity of Wheat Metabolome.

Wheat is a widely cultivated cereal, consumed by nearly 80% of the total population in the world. Although wheat is growing on 215 million hectares annually, its production is still inadequate to meet the future demand of feeding the 10 billion human population. Global food security is the biggest challenge as climate change is threatening crop production. There is a need to fast-- track the wheat breeding by devising modern biotechnological tools. Climate-smart wheat having greater stress resilience, better adaptability and improved agronomic traits are vital to guarantee food security. Substantial understanding and knowledge of vital biochemical pathways and regulatory networks is required for achieving stress resilience in wheat. Metabolomics has emerged as a fascinating technology to speed up the crop improvement programs by deciphering unique metabolic pathways for abiotic/biotic stress tolerance. State-of-the-art metabolomics tools such as nuclear magnetic resonance (NMR) and advanced mass spectrometry (MS) has opened new horizons for detailed analysis of wheat metabolome. The identification of unique metabolic pathways offers various types of stress tolerance and helps to screen the elite wheat cultivars. In this review, we summarize the applications of metabolomics to probe the stress-responsive metabolites and stress-inducive regulatory pathways that govern abiotic/biotic stress tolerance in wheat and highlight the significance of metabolic profiling to characterize wheat agronomics traits. Furthermore, we also describe the potential of metabolomics-assisted speed breeding for wheat improvement and propose future directions.

Application of UPLC-QTOF-MS Based Untargeted Metabolomics in Identification of Metabolites Induced in Pathogen-Infected Rice.

Metabolomics is a useful tool for comparing metabolite changes in plants. Because of its high sensitivity, metabolomics combined with high-resolution mass spectrometry (HR-MS) is the most widely accepted metabolomics tools. In this study, we compared the metabolites of pathogen-infected rice (Oryza sativa) with control rice using an untargeted metabolomics approach. We profiled the mass features of two rice groups using a liquid chromatography quadrupole time-of-flight mass spectrometry (QTOF-MS) system. Twelve of the most differentially induced metabolites in infected rice were selected through multivariate data analysis and identified through a mass spectral database search. The role of these compounds in metabolic pathways was finally investigated using pathway analysis. Our study showed that the most frequently induced secondary metabolites are prostanoids, a subclass of eicosanoids, which are associated with plant defense metabolism against pathogen infection. Herein, we propose a new untargeted metabolomics approach for understanding plant defense system at the metabolic level.

A Practical Guide to Metabolomics Software Development.

A growing number of software tools have been developed for metabolomics data processing and analysis. Many new tools are contributed by metabolomics practitioners who have limited prior experience with software development, and the tools are subsequently implemented by users with expertise that ranges from basic point-and-click data analysis to advanced coding. This Perspective is intended to introduce metabolomics software users and developers to important considerations that determine the overall impact of a publicly available tool within the scientific community. The recommendations reflect the collective experience of an NIH-sponsored Metabolomics Consortium working group that was formed with the goal of researching guidelines and best practices for metabolomics tool development. The recommendations are aimed at metabolomics researchers with little formal background in programming and are organized into three stages: (i) preparation, (ii) tool development, and (iii) distribution and maintenance.

Dynamics of Chemical Diversity during Co‐Cultures: An Integrative Time‐Scale Metabolomics Study of Fungal Endophytes Cophinforma mamane and Fusarium solani

A rapid and efficient metabolomic study of Cophinforma mamane and Fusarium solani co-cultivation in time-series based analysis was developed to study metabolome variations during their fungal interactions. The fungal metabolomes were studied through the integration of four metabolomic tools: MS-DIAL, a chromatographic deconvolution of liquid-chromatography-mass spectrometry (LC/MS); MS-FINDER, a structure-elucidation program with a wide range metabolome database; GNPS, an effective method to organize MS/MS fragmentation spectra, and MetaboAnalyst, a comprehensive web application for metabolomic data analysis and interpretation. Co-cultures of C. mamane and F. solani induced different patterns of metabolite production over 10 days of incubation and induced production of five de novo compounds not occurring in monocultures. These results emphasize that co-culture in time-frame analysis is an interesting method to unravel hidden metabolome in the investigation of fungal chemodiversity.

The Role of Chromatographic and Electromigration Techniques in Foodomics.

Foodomics is the discipline aimed at studying the prevention of diseases by food, identifying chemical, biological and biochemical food contaminants, determining changes in genetically modified foods, identifying biomarkers able to confirm the authenticity and quality of foods or studying the safety, quality and traceability of foods, among other issues. It is mainly based on the use of genomic, transcriptomic, proteomic and metabolomic tools, among others, in order to understand the effect of food on animals and humans at the level of genes, messenger ribonucleic acid, proteins and metabolites. Since the first definition of Foodomics, a reasonable number of works have shown the extremely high possibilities of this discipline, which is highly based on the use of advanced analytical hyphenated techniques - especially for proteomics and metabolomics. This book chapter aims at providing a general description of the role of chromatographic and electromigration techniques that are currently being applied to achieve the main objectives of Foodomics, particularly in the proteomic and metabolomic fields, since most published works have been focused on these approaches, and to highlight relevant applications.

Metabolomics Signatures of SARS-CoV-2 Infection.

For a very long time, viral infections have been considered as one of the most important causes of death and disability around the world. Through the viral infection, viruses as small pathogens enter the host cells and use hosts' biosynthesis machinery to replicate and collect infectious lineages. Moreover, they can modify hosts' metabolic pathways in order to their own purposes. Nowadays (in 2019-2020), the most famous type of viral infection which was caused by a novel type of coronavirus is called COVID-19 disease. It has claimed the lives of many people around the world and is a very serious threat to health. Since investigations of the effects of viruses on host metabolism using metabolomics tools may have given focuses on novel appropriate treatments, in the current review the authors highlighted the virus-host metabolic interactions and metabolomics perspective in COVID-19.

Genomics- and Metabolomics-Based Investigation of the Deep-Sea Sediment-Derived Yeast, Rhodotorula mucilaginosa 50-3-19/20B.

Red yeasts of the genus Rhodotorula are of great interest to the biotechnological industry due to their ability to produce valuable natural products, such as lipids and carotenoids with potential applications as surfactants, food additives, and pharmaceuticals. Herein, we explored the biosynthetic potential of R. mucilaginosa 50-3-19/20B collected from the Mid-Atlantic Ridge using modern genomics and untargeted metabolomics tools. R. mucilaginosa 50-3-19/20B exhibited anticancer activity when grown on PDA medium, while antimicrobial activity was observed when cultured on WSP-30 medium. Applying the bioactive molecular networking approach, the anticancer activity was linked to glycolipids, namely polyol esters of fatty acid (PEFA) derivatives. We purified four PEFAs (1–4) and the known methyl-2-hydroxy-3-(1H-indol-2-yl)propanoate (5). Their structures were deduced from NMR and HR-MS/MS spectra, but 1–5 showed no anticancer activity in their pure form. Illumina-based genome sequencing, de novo assembly and standard biosynthetic gene cluster (BGC) analyses were used to illustrate key components of the PEFA biosynthetic pathway. The fatty acid producing BGC3 was identified to be capable of producing precursors of PEFAs. Some Rhodotorula strains are able to convert inulin into high-yielding PEFA and cell lipid using a native exo-inulinase enzyme. The genomic locus for an exo-inulinase enzyme (g1629.t1), which plays an instrumental role in the PEFA production via the mannitol biosynthesis pathway, was identified. This is the first untargeted metabolomics study on R. mucilaginosa providing new genomic insights into PEFA biosynthesis.