Megan Showalter

Identification of small molecules using accurate mass MS/MS search

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS2 to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography–mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography–mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

Epimetabolites: discovering metabolism beyond building and burning

Enzymatic transformations of primary, canonical metabolites generate active biomolecules that regulate important cellular and physiological processes. Roles include regulation of histone demethylation in epigenetics, inflammation in tissue injury, insulin sensitivity, cancer cell invasion, stem cell pluripotency status, inhibition of nitric oxide signaling and others. Such modified compounds, defined as epimetabolites, have functions distinct from classic hormones as well as removed from generic anabolism and catabolism. Epimetabolites are discovered by untargeted metabolomics using liquid- or gas chromatography-high resolution mass spectrometry and structurally annotated by in-silico fragmentation prediction tools. Their specific biological functions are subsequently investigated by targeted metabolomics methods.

Metabolomic characteristics of cholesterol-induced non-obese nonalcoholic fatty liver disease in mice

Nonalcoholic fatty liver disease (NAFLD) in non-obese patients remains a clinical condition with unclear etiology and pathogenesis. Using a metabolomics approach in a mouse model that recapitulates almost all the characteristic features of non-obese NAFLD, we aimed to advance mechanistic understanding of this disorder. Mice fed high fat, high cholesterol, cholate (HFHCC) diet for three weeks consistently developed hepatic pathology similar to NAFLD and nonalcoholic steatohepatitis (NASH) without changes to body weight or fat pad weights. Gas- and liquid chromatography/mass spectrometry-based profiling of lipidomic and primary metabolism changes in the liver and plasma revealed that systemic mechanisms leading to steatosis and hepatitis in this non-obese NAFLD model were driven by a combination of effects directed by elevated free cholesterol, cholesterol esters and cholic acid, and associated changes to metabolism of sphingomyelins and phosphatidylcholines. These results demonstrate that mechanisms underlying cholesterol-induced non-obese NAFLD are distinct from NAFLD occurring as a consequence of metabolic syndrome. In addition, this investigation provides one of the first metabolite reference profiles for interpreting effects of dietary and hepatic cholesterol in human non-obese NAFLD/NASH patients.

Registered report: The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate

The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of selected experiments from a number of high-profile papers in the field of cancer biology. The papers, which were published between 2010 and 2012, were selected on the basis of citations and Altmetric scores (Errington et al., 2014). This Registered Report describes the proposed replication plan of key experiments from “The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate” by Ward and colleagues, published in Cancer Cell in 2010 (Ward et al., 2010). The experiments that will be replicated are those reported in Figures 2, 3 and 5. Ward and colleagues demonstrate the mutations in isocitrate dehydrogenase 2 (IDH2), commonly found in acute myeloid leukemia (AML), abrogate the enzyme’s wild-type activity and confer to the mutant neomorphic activity that produces the oncometabolite 2-hydroxyglutarate (2-HG) (Figures 2 and 3). They then show that elevated levels of 2-HG are correlated with mutations in IDH1 and IDH2 in AML patient samples (Figure 5). The Reproducibility Project: Cancer Biology is a collaboration between the Center for Open Science and Science Exchange and the results of the replications will be published by eLife. DOI: http://dx.doi.org/10.7554/eLife.12626.001

Obesogenic diets alter metabolism in mice.

Obesity and accompanying metabolic disease is negatively correlated with lung health yet the exact mechanisms by which obesity affects the lung are not well characterized. Since obesity is associated with lung diseases as chronic bronchitis and asthma, we designed a series of experiments to measure changes in lung metabolism in mice fed obesogenic diets. Mice were fed either control or high fat/sugar diet (45%kcal fat/17%kcal sucrose), or very high fat diet (60%kcal fat/7% sucrose) for 150 days. We performed untargeted metabolomics by GC-TOFMS and HILIC-QTOFMS and lipidomics by RPLC-QTOFMS to reveal global changes in lung metabolism resulting from obesity and diet composition. From a total of 447 detected metabolites, we found 91 metabolite and lipid species significantly altered in mouse lung tissues upon dietary treatments. Significantly altered metabolites included complex lipids, free fatty acids, energy metabolites, amino acids and adenosine and NAD pathway members. While some metabolites were altered in both obese groups compared to control, others were different between obesogenic diet groups. Furthermore, a comparison of changes between lung, kidney and liver tissues indicated few metabolic changes were shared across organs, suggesting the lung is an independent metabolic organ. These results indicate obesity and diet composition have direct mechanistic effects on composition of the lung metabolome, which may contribute to disease progression by lung-specific pathways.

Mesenchymal stem cell-based therapy for ischemic stroke

Ischemic stroke represents a major, worldwide health burden with increasing incidence. Patients affected by ischemic strokes currently have few clinically approved treatment options available. Most currently approved treatments for ischemic stroke have narrow therapeutic windows, severely limiting the number of patients able to be treated. Mesenchymal stem cells represent a promising novel treatment for ischemic stroke. Numerous studies have demonstrated that mesenchymal stem cells functionally improve outcomes in rodent models of ischemic stroke. Recent studies have also shown that exosomes secreted by mesenchymal stem cells mediate much of this effect. In the present review, we summarize the current literature on the use of mesenchymal stem cells to treat ischemic stroke. Further studies investigating the mechanisms underlying mesenchymal stem cells tissue healing effects are warranted and would be of benefit to the field.

Advances in Mass Spectrometry for Food Authenticity Testing: An Omics Perspective

Recent advances in mass spectrometry have led to the development of novel methods applicable in food chemistry and technology. Specifically, mass spectrometry-based omics sciences have introduced high-throughput methods permitting complex assessment of food authenticity and detection of adulteration. In this chapter, we focus mainly on mass spectrometry-based omics approaches such as (1) proteomics and peptidomics for targeting large-molecular-weight compounds and (2) metabolomics and lipidomics for studying small molecules in different food commodities (meat, fish, milk, cheese, wine, beer, coffee, honey, and olive oil). Emphasis has been placed on studies with either a large number of samples, to maximize the chance of obtaining robust statistical models, or where high species-specific selectivity was reported.

ASSOCIATION OF SERUM LIPIDS WITH ALZHEIMER'S DISEASE IN THE ADNI COHORT: AN UNTARGETED LIPIDOMICS STUDY

Department of Statistics, North Carolina State University, Raleigh, NC, USA; Helmholtz Zentrum Muenchen, Oberschleißheim, Germany; German Center for Diabetes Research, Neuherberg, Germany; Duke Institute of Brain Sciences, Duke University, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Department of Medicine, Duke University, Durham, NC, USA; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands. Contact e-mail: s.ahmad@erasmusmc.nl