Charmion Cruickshank-Quinn

Effects of sodium nitrite supplementation on vascular function and related small metabolite signatures in middle-aged and older adults

Insufficient nitric oxide (NO) bioavailability plays an important role in endothelial dysfunction and arterial stiffening with aging. Supplementation with sodium nitrite, a precursor of NO, ameliorates age-related vascular endothelial dysfunction and arterial stiffness in mice, but effects on humans, including the metabolic pathways altered, are unknown. The purpose of this study was to determine the safety, feasibility, and efficacy of oral sodium nitrite supplementation for improving vascular function in middle-aged and older adults and to identify related circulating metabolites. Ten weeks of sodium nitrite (80 or 160 mg/day, capsules, TheraVasc; randomized, placebo control, double blind) increased plasma nitrite acutely (5- to 15-fold, P < 0.001 vs. placebo) and chronically (P < 0.10) and was well tolerated without symptomatic hypotension or clinically relevant elevations in blood methemoglobin. Endothelial function, measured by brachial artery flow-mediated dilation, increased 45-60% vs. baseline (P < 0.10) without changes in body mass or blood lipids. Measures of carotid artery elasticity (ultrasound and applanation tonometry) improved (decreased β-stiffness index, increased cross-sectional compliance, P < 0.05) without changes in brachial or carotid artery blood pressure. Aortic pulse wave velocity was unchanged. Nitrite-induced changes in vascular measures were significantly related to 11 plasma metabolites identified by untargeted analysis. Baseline abundance of multiple metabolites, including glycerophospholipids and fatty acyls, predicted vascular changes with nitrite. This study provides evidence that sodium nitrite supplementation is well tolerated, increases plasma nitrite concentrations, improves endothelial function, and lessens carotid artery stiffening in middle-aged and older adults, perhaps by altering multiple metabolic pathways, thereby warranting a larger clinical trial.

MSPrep—Summarization, normalization and diagnostics for processing of mass spectrometry–based metabolomic data

MOTIVATION Although R packages exist for the pre-processing of metabolomic data, they currently do not incorporate additional analysis steps of summarization, filtering and normalization of aligned data. We developed the MSPrep R package to complement other packages by providing these additional steps, implementing a selection of popular normalization algorithms and generating diagnostics to help guide investigators in their analyses. AVAILABILITY http://www.sourceforge.net/projects/msprep

Transient and persistent metabolomic changes in plasma following chronic cigarette smoke exposure in a mouse model.

Cigarette smoke exposure is linked to the development of a variety of chronic lung and systemic diseases in susceptible individuals. Metabolomics approaches may aid in defining disease phenotypes, may help predict responses to treatment, and could identify biomarkers of risk for developing disease. Using a mouse model of chronic cigarette smoke exposure sufficient to cause mild emphysema, we investigated whether cigarette smoke induces distinct metabolic profiles and determined their persistence following smoking cessation. Metabolites were extracted from plasma and fractionated based on chemical class using liquid-liquid and solid-phase extraction prior to performing liquid chromatography mass spectrometry-based metabolomics. Metabolites were evaluated for statistically significant differences among group means (p-value≤0.05) and fold change ≥1.5). Cigarette smoke exposure was associated with significant differences in amino acid, purine, lipid, fatty acid, and steroid metabolite levels compared to air exposed animals. Whereas 60% of the metabolite changes were reversible, 40% of metabolites remained persistently altered even following 2 months of smoking cessation, including nicotine metabolites. Validation of metabolite species and translation of these findings to human plasma metabolite signatures induced by cigarette smoking may lead to the discovery of biomarkers or pathogenic pathways of smoking-induced disease.

Gene and metabolite time-course response to cigarette smoking in mouse lung and plasma

Prolonged cigarette smoking (CS) causes chronic obstructive pulmonary disease (COPD), a prevalent serious condition that may persist or progress after smoking cessation. To provide insight into how CS triggers COPD, we investigated temporal patterns of lung transcriptome expression and systemic metabolome changes induced by chronic CS exposure and smoking cessation. Whole lung RNA-seq data was analyzed at transcript and exon levels from C57Bl/6 mice exposed to CS for 1- or 7 days, for 3-, 6-, or 9 months, or for 6 months followed by 3 months of cessation using age-matched littermate controls. We identified previously unreported dysregulation of pyrimidine metabolism and phosphatidylinositol signaling pathways and confirmed alterations in glutathione metabolism and circadian gene pathways. Almost all dysregulated pathways demonstrated reversibility upon smoking cessation, except the lysosome pathway. Chronic CS exposure was significantly linked with alterations in pathways encoding for energy, phagocytosis, and DNA repair and triggered differential expression of genes or exons previously unreported to associate with CS or COPD, including Lox, involved in matrix remodeling, Gp2, linked to goblet cells, and Slc22a12 and Agpat3, involved in purine and glycerolipid metabolism, respectively. CS-induced lung metabolic pathways changes were validated using metabolomic profiles of matched plasma samples, indicating that dynamic metabolic gene regulation caused by CS is reflected in the plasma metabolome. Using advanced technologies, our study uncovered novel pathways and genes altered by chronic CS exposure, including those involved in pyrimidine metabolism, phosphatidylinositol signaling and lysosome function, highlighting their potential importance in the pathogenesis or diagnosis of CS-associated conditions.

Performance of a High-Pressure Liquid Chromatography-Ion Mobility-Mass Spectrometry System for Metabolic Profiling

A commercial liquid chromatography/drift tube ion mobility-mass spectrometer (LC/IM-MS) was evaluated for its utility in global metabolomics analysis. Performance was assessed using 12 targeted metabolite standards where the limit of detection (LOD), linear dynamic range, resolving power, and collision cross section (Ω) are reported for each standard. Data were collected in three different instrument operation modes: flow injection analysis with IM-MS (FIA/IM-MS), LC/MS, and LC/IM-MS. Metabolomics analyses of human plasma and HaCaT cells were used to compare the above three operation modes. LC/MS provides linearity in response, data processing automation, improved limits of detection, and ease of use. Advantages of LC/IM-MS and FIA/IM-MS include the ability to develop mobility-mass trend lines for structurally similar biomolecules, increased peak capacity, reduction of chemical/matrix noise, improvement in signal-to-noise, and separations of isobar/isomer compounds that are not resolved by LC. We further tested the feasibility of incorporating IM-MS into conventional LC/MS metabolomics workflows. In general, the addition of ion mobility dimension has increased the separation of compounds in complex biological matrixes and has the potential to largely improve the throughput of metabolomics analysis.

Dysregulation of Metabolic Pathways in a Mouse Model of Allergic Asthma

Asthma is a complex lung disease resulting from the interplay of genetic and environmental factors. To understand the molecular changes that occur during the development of allergic asthma without genetic and environmental confounders, an experimental model of allergic asthma in mice was used. Our goals were to (1) identify changes at the small molecule level due to allergen exposure, (2) determine perturbed pathways due to disease, and (3) determine whether small molecule changes correlate with lung function.

Exploratory Metabolomics Profiling in the Kainic Acid Rat Model Reveals Depletion of 25-Hydroxyvitamin D3 during Epileptogenesis

Currently, no reliable markers are available to evaluate the epileptogenic potential of a brain injury. The electroencephalogram is the standard method of diagnosis of epilepsy; however, it is not used to predict the risk of developing epilepsy. Biomarkers that indicate an individual’s risk to develop epilepsy, especially those measurable in the periphery are urgently needed. Temporal lobe epilepsy (TLE), the most common form of acquired epilepsy, is characterized by spontaneous recurrent seizures following brain injury and a seizure-free “latent” period. Elucidation of mechanisms at play during epilepsy development (epileptogenesis) in animal models of TLE could enable the identification of predictive biomarkers. Our pilot study using liquid chromatography-mass spectrometry metabolomics analysis revealed changes (p-value ≤ 0.05, ≥1.5-fold change) in lipid, purine, and sterol metabolism in rat plasma and hippocampus during epileptogenesis and chronic epilepsy in the kainic acid model of TLE. Notably, disease development was associated with dysregulation of vitamin D3 metabolism at all stages and plasma 25-hydroxyvitamin D3 depletion in the acute and latent phase of injury-induced epileptogenesis. These data suggest that plasma VD3 metabolites reflect the severity of an epileptogenic insult and that a panel of plasma VD3 metabolites may be able to serve as a marker of epileptogenesis.

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis

Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl. Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.

Metabolomic similarities between bronchoalveolar lavage fluid and plasma in humans and mice

This observational study catalogues the overlap in metabolites between matched bronchoalveolar lavage fluid (BALF) and plasma, identifies the degree of congruence between these metabolomes in human and mouse, and determines how molecules may change in response to cigarette smoke (CS) exposure. Matched BALF and plasma was collected from mice (ambient air or CS-exposed) and humans (current or former smokers), and analyzed using mass spectrometry. There were 1155 compounds in common in all 4 sample types; fatty acyls and glycerophospholipids strongly overlapped between groups. In humans and mice, more than half of the metabolites present in BALF were also present in plasma. Mouse BALF and human BALF had a strong positive correlation with 2040 metabolites in common, suggesting that mouse models can be used to interrogate human lung metabolome changes. While power was affected by small sample size in the mouse study, the BALF metabolome appeared to be more affected by CS than plasma. CS-exposed mice showed increased plasma and BALF glycerolipids and glycerophospholipids. This is the first report cataloguing the metabolites present across mouse and human, BALF and plasma. Findings are relevant to translational studies where mouse models are used to examine human disease, and where plasma may be interrogated in lieu of BALF or lung tissue.

A prototypic small molecule database for bronchoalveolar lavage-based metabolomics

The analysis of bronchoalveolar lavage fluid (BALF) using mass spectrometry-based metabolomics can provide insight into lung diseases, such as asthma. However, the important step of compound identification is hindered by the lack of a small molecule database that is specific for BALF. Here we describe prototypic, small molecule databases derived from human BALF samples (n=117). Human BALF was extracted into lipid and aqueous fractions and analyzed using liquid chromatography mass spectrometry. Following filtering to reduce contaminants and artifacts, the resulting BALF databases (BALF-DBs) contain 11,736 lipid and 658 aqueous compounds. Over 10% of these were found in 100% of samples. Testing the BALF-DBs using nested test sets produced a 99% match rate for lipids and 47% match rate for aqueous molecules. Searching an independent dataset resulted in 45% matching to the lipid BALF-DB compared to<25% when general databases are searched. The BALF-DBs are available for download from MetaboLights. Overall, the BALF-DBs can reduce false positives and improve confidence in compound identification compared to when general databases are used.