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.

Hypoxia has long been implicated in the pathogenesis of fibrotic diseases. Aberrantly activated myofibroblasts are the primary pathological driver of fibrotic progression, yet how various microenvironmental influences, such as hypoxia, contribute to their sustained activation and differentiation is poorly understood. As a defining feature of hypoxia is its impact on cellular metabolism, we sought to investigate how hypoxia-induced metabolic reprogramming affects myofibroblast differentiation and fibrotic progression, and to test the preclinical efficacy of targeting glycolytic metabolism for the treatment of pulmonary fibrosis. Bleomycin-induced pulmonary fibrotic progression was evaluated in two independent, fibroblast-specific, promoter-driven, hypoxia-inducible factor (Hif) 1A knockout mouse models and in glycolytic inhibitor, dichloroacetate-treated mice. Genetic and pharmacological approaches were used to explicate the role of metabolic reprogramming in myofibroblast differentiation. Hypoxia significantly enhanced transforming growth factor-β–induced myofibroblast differentiation through HIF-1α, whereas overexpression of the critical HIF-1α–mediated glycolytic switch, pyruvate dehydrogenase kinase 1 (PDK1) was sufficient to activate glycolysis and potentiate myofibroblast differentiation, even in the absence of HIF-1α. Inhibition of the HIF-1α/PDK1 axis by genomic deletion of Hif1A or pharmacological inhibition of PDK1 significantly attenuated bleomycin-induced pulmonary fibrosis. Our findings suggest that HIF-1α/PDK1–mediated glycolytic reprogramming is a critical metabolic alteration that acts to promote myofibroblast differentiation and fibrotic progression, and demonstrate that targeting glycolytic metabolism may prove to be a potential therapeutic strategy for the treatment of pulmonary fibrosis.

Metabolomics, along with other “omics” approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages.

The purpose of this project was to identify metabolites, proteins, genes, and promoters associated with water stress responses in soybean. A number of these may serve as new targets for the biotechnological improvement of drought responses in soybean (Glycine max). We identified metabolites, proteins, and genes that are strongly up or down regulated during rapid water stress following removal from a hydroponics system. 163 metabolites showed significant changes during water stress in roots and 93 in leaves. The largest change was a root-specific 160-fold increase in the coumestan coumestrol making it a potential biomarker for drought and a promising target for improving drought responses. Previous reports suggest that coumestrol stimulates mycorrhizal colonization and under certain conditions mycorrhizal plants have improved drought tolerance. This suggests that coumestrol may be part of a call for help to the rhizobiome during stress. About 3,000 genes were strongly up-regulated by drought and we identified regulators such as ERF, MYB, NAC, bHLH, and WRKY transcription factors, receptor-like kinases, and calcium signaling components as potential targets for soybean improvement as well as the jasmonate and abscisic acid biosynthetic genes JMT, LOX1, and ABA1. Drought stressed soybean leaves show reduced mRNA levels of stomatal development genes including FAMA-like, MUTE-like and SPEECHLESS-like bHLH transcription factors and leaves formed after drought stress had a reduction in stomatal density of 22.34 % and stomatal index of 17.56 %. This suggests that reducing stomatal density may improve drought tolerance. MEME analyses suggest that ABRE (CACGT/CG), CRT/DRE (CCGAC) and a novel GTGCnTGC/G element play roles in transcriptional activation and these could form components of synthetic promoters to drive expression of transgenes. Using transformed hairy roots, we validated the increase in promoter activity of GmWRKY17 and GmWRKY67 during dehydration and after 20 μM ABA treatment. Our toolbox provides new targets and strategies for improving soybean drought tolerance and includes the coumestan coumestrol, transcription factors that regulate stomatal density, water stress-responsive WRKY gene promoters and a novel DNA element that appears to be enriched in water stress responsive promoters.

Rosaceae include numerous economically important and morphologically diverse species. Comparative mapping between the member species in Rosaceae have indicated some level of synteny. Recently the whole genome of three crop species, peach, apple and strawberry, which belong to different genera of the Rosaceae family, have been sequenced, allowing in-depth comparison of these genomes.