Metabolomic Method UPLC-q-ToF Polar and Non-polar Metabolites in the Healthy Rat Cerebellum Using an In-Vial Dual Extraction

Unbiased metabolomic analysis of biological samples is a powerful and increasingly commonly utilised tool, especially for the analysis of bio-fluids to identify candidate biomarkers. To date however only a small number of metabolomic studies have been applied to studying the metabolite composition of tissue samples, this is due, in part to a number of technical challenges including scarcity of material and difficulty in extracting metabolites. The aim of this study was to develop a method for maximising the biological information obtained from small tissue samples by optimising sample preparation, LC-MS analysis and metabolite identification. Here we describe an in-vial dual extraction (IVDE) method, with reversed phase and hydrophilic liquid interaction chromatography (HILIC) which reproducibly measured over 4,000 metabolite features from as little as 3mg of brain tissue. The aqueous phase was analysed in positive and negative modes following HILIC separation in which 2,838 metabolite features were consistently measured including amino acids, sugars and purine bases. The non-aqueous phase was also analysed in positive and negative modes following reversed phase separation gradients respectively from which 1,183 metabolite features were consistently measured representing metabolites such as phosphatidylcholines, sphingolipids and triacylglycerides. The described metabolomics method includes a database for 200 metabolites, retention time, mass and relative intensity, and presents the basal metabolite composition for brain tissue in the healthy rat cerebellum

Association between fatty acid metabolism in the brain and Alzheimer disease neuropathology and cognitive performance:A nontargeted metabolomic study

BACKGROUND:The metabolic basis of Alzheimer disease (AD) pathology and expression of AD symptoms is poorly understood. Omega-3 and -6 fatty acids have previously been linked to both protective and pathogenic effects in AD. However, to date little is known about how the abundance of these species is affected by differing levels of disease pathology in the brain. METHODS AND FINDINGS:We performed metabolic profiling on brain tissue samples from 43 individuals ranging in age from 57 to 95 y old who were stratified into three groups: AD (N = 14), controls (N = 14) and "asymptomatic Alzheimer's disease" (ASYMAD), i.e., individuals with significant AD neuropathology at death but without evidence for cognitive impairment during life (N = 15) from the autopsy sample of the Baltimore Longitudinal Study of Aging (BLSA). We measured 4,897 metabolite features in regions both vulnerable in the middle frontal and inferior temporal gyri (MFG and ITG) and resistant (cerebellum) to classical AD pathology. The levels of six unsaturated fatty acids (UFAs) in whole brain were compared in controls versus AD, and the differences were as follows: linoleic acid (p = 8.8 x 10-8, FC = 0.52, q = 1.03 x 10-6), linolenic acid (p = 2.5 x 10-4, FC = 0.84, q = 4.03 x 10-4), docosahexaenoic acid (p = 1.7 x 10-7, FC = 1.45, q = 1.24 x 10-6), eicosapentaenoic acid (p = 4.4 x 10-4, FC = 0.16, q = 6.48 x 10-4), oleic acid (p = 3.3 x 10-7, FC = 0.34, q = 1.46 x 10-6), and arachidonic acid (p = 2.98 x 10-5, FC = 0.75, q = 7.95 x 10-5). These fatty acids were strongly associated with AD when comparing the groups in the MFG and ITG, respectively: linoleic acid (p ASYMAD>AD) and increases in docosahexanoic acid (AD>ASYMAD>control) may represent regionally specific threshold levels of these metabolites beyond which the accumulation of AD pathology triggers the expression of clinical symptoms. The main limitation of this study is the relatively small sample size. There are few cohorts with extensive longitudinal cognitive assessments during life and detailed neuropathological assessments at death, such as the BLSA. CONCLUSIONS:The findings of this study suggest that unsaturated fatty acid metabolism is significantly dysregulated in the brains of patients with varying degrees of Alzheimer pathology

Measured metabolite features in the reversed phase method in experiment 1.

<p>Showing the number of metabolite peaks identified and their relative variability in 100%, 85% and 70% of 7 sample replicates.</p><p>^a percentage of samples a peak is detected in</p><p>^b coefficient of variance of peak intensity between samples.</p><p>Measured metabolite features in the reversed phase method in experiment 1.</p

Plots of sample mass in milligrams against intensity for 9 annotated metabolites.

<p>A) taurine B) hypoxanthine C) glutamate D) pantothenate E) aspartate F) glcosylceramide (36:1) G) phosphatidylethanolamine (38:4) H) ceramide (38:1) I) triglyceride (48:3).</p

Graphical representation of the experimental designs used.

<p>A) experiment 1, a single 18mg brain section was homogenised then 7 parallel extractions were performed on 50μl aliquots of homogenate. B) Experiment 2, brain sections ranging from 3–17mg were homogenised and extracted parallel.</p

Applied analytical pipeline.

<p>Shows the seven steps from tissue sectioning to IVDE and onto data processing and multivariate analysis of variation.</p

Recoveries of HILIC and reversed phase internal standards in experiment 2.

<p>A) plot of intensity of reversed phase internal standards Heptsdecanoic acid (negative) and Tripentadecanoin (positive), B) plot of intensity of HILIC internal standards in positive ionisation mode, C) plot of intensity of HILIC internal standards in negative ionisation mode, D) average intensity and coefficient of variance of all internal standards.</p

Boxplots showing the effect of disease status on the abundance of six UFAs in the CB, ITG, and MFG.

<p>Dysregulation of six UFAs shown by boxplots of three disease statuses separated by brain region A) arachidonic acid (AA), B) oleic acid (OLA), C) eicosapentaenoic acid (EPA), D) linolenic acid (LNA), E) linoleic acid (LA), F) docosahexaenoic acid (DHA). AS, asymptomatic Alzheimer; CN, control; DM, Dementia/Alzheimer.</p