Protocol for mapping the metabolome and lipidome of medulloblastoma cells using liquid chromatography-mass spectrometry

Summary: Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and lipidomics have recently been used to show that MYC-amplified group 3 medulloblastoma tumors are driven by metabolic reprogramming. Here, we present a protocol to extract metabolites and lipids from human medulloblastoma brain tumor-initiating cells and normal neural stem cells. We describe untargeted LC-MS methods that can be used to achieve extensive coverage of the polar metabolome and lipidome. Finally, we detail strategies for metabolite identification and data analysis.For complete details on the use and execution of this protocol, please refer to Gwynne et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics

Aqueous Epoxide Ring-Opening Polymerization (AEROP): Green Synthesis of Polyglycidol with Ultralow Branching

A green synthesis method for the preparation of polyglycidol in buffer with a high degree of control is presented. Polymerizations were conducted in phosphate buffered saline (PBS) of varying pH 3.8, 6.0, and 8.0 and deionized water at temperatures of 60, 80, and 100 °C. Taking advantage of the catalytic reactivity between water and glycidol afforded a novel green polymerization technique for the facile synthesis of polyglycidol systems with semibranched architectures with a degree of branching (DB) of 0.24, which situates the polymers between purely linear (DB = 0) and hyperbranched (DB = 0.56–0.63) systems. This method sidesteps the strenuous polymerization conditions required for most polyglycidol structures and provides well-controlled and reproducible species with a high degree of linearity and narrow polydispersities of 1.1–1.2 via the first green and nonexothermic synthesis of polyglycidol

Drug-Initiated Activity Metabolomics Identifies Myristoylglycine as a Potent Endogenous Metabolite for Human Brown Fat Differentiation

Worldwide, obesity rates have doubled since the 1980s and in the USA alone, almost 40% of adults are obese, which is closely associated with a myriad of metabolic diseases such as type 2 diabetes and arteriosclerosis. Obesity is derived from an imbalance between energy intake and consumption, therefore balancing energy homeostasis is an attractive target for metabolic diseases. One therapeutic approach consists of increasing the number of brown-like adipocytes in the white adipose tissue (WAT). Whereas WAT stores excess energy, brown adipose tissue (BAT) can dissipate this energy overload in the form of heat, increasing energy expenditure and thus inhibiting metabolic diseases. To facilitate BAT production a high-throughput screening approach was developed on previously known drugs using human Simpson–Golabi–Behmel Syndrome (SGBS) preadipocytes. The screening allowed us to discover that zafirlukast, an FDA-approved small molecule drug commonly used to treat asthma, was able to differentiate adipocyte precursors and white-biased adipocytes into functional brown adipocytes. However, zafirlukast is toxic to human cells at higher dosages. Drug-Initiated Activity Metabolomics (DIAM) was used to investigate zafirlukast as a BAT inducer, and the endogenous metabolite myristoylglycine was then discovered to mimic the browning properties of zafirlukast without impacting cell viability. Myristoylglycine was found to be bio-synthesized upon zafirlukast treatment and was unique in inducing brown adipocyte differentiation, raising the possibility of using endogenous metabolites and bypassing the exogenous drugs to potentially alleviate disease, in this case, obesity and other related metabolic diseases

Unusual Kinetic Isotope Effects of Deuterium Reinforced Polyunsaturated Fatty Acids in Tocopherol-Mediated Free Radical Chain Oxidations

Substitution of -CD2- at the reactive centers of linoleic and linolenic acids reduces the rate of abstraction of D by a tocopheryl radical by as much as 36-fold, compared to the abstraction of H from a corresponding -CH2- center. This H atom transfer reaction is the rate-determining step in the tocopherol-mediated peroxidation of lipids in human low-density lipoproteins, a process that has been linked to coronary artery disease. The unanticipated large kinetic isotope effects reported here for the tocopherol-mediated oxidation of linoleic and linolenic acids and esters suggests that tunneling makes this process favorable

Unusual Kinetic Isotope Effects of Deuterium Reinforced Polyunsaturated Fatty Acids in Tocopherol-Mediated Free Radical Chain Oxidations

Substitution of −CD₂– at the reactive centers of linoleic and linolenic acids reduces the rate of abstraction of D by a tocopheryl radical by as much as 36-fold, compared to the abstraction of H from a corresponding −CH₂– center. This H atom transfer reaction is the rate-determining step in the <i>tocopherol-mediated peroxidation</i> of lipids in human low-density lipoproteins, a process that has been linked to coronary artery disease. The unanticipated large kinetic isotope effects reported here for the tocopherol-mediated oxidation of linoleic and linolenic acids and esters suggests that tunneling makes this process favorable

Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes

The speed and throughput of analytical platforms has been a driving force in recent years in the “omics” technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism

Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e., the “exposome”, and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700 000 chemical structures to now include more than 950 000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis, and further, artificial intelligence provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the methodological challenges current exposomics research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health