The Frog Data Tutorial is an example of a metabolomics analysis of the skin of the Alpine Tree Frog. In a controlled study, the skin was exposed to the Chytrid fungus Batrachochytrium dendrobatidis (Bd), leading to Chytridiomycosis. Chytridiomycosis is an infectious disease that affects amphibians worldwide. Bd is capable of causing sporadic deaths in some amphibian populations and results in 100 per cent mortality in others. Using an untargeted GC-MS-based metabolomics approach, it is hoped that an improved understanding of the molecular basis underlying the pathophysiology of chytridiomycosis can be determined. The findings will be fundamental for i) explaining differences in population susceptibility, and ii) identifying targets for intervention and improved management.
The Frog Data Tutorial provides instructions for using AnalyzerPro for metabolomics data processing. Data is provided for a subset of samples from a larger study [three controls (Frog 1-3) and three infected animals (Frog 4-6)]. In this tutorial, this data set is used to teach you the basic steps necessary to use AnalyzerPro and familiarise yourself with metabolomics data, and basic metabolomics analyses. These samples were homogenised and metabolites were extracted using organic solvents and water. The metabolite extracts were freeze-dried and chemically modified (derivatised) to make the metabolites amenable to analysis by GC-MS. The data was acquired using a Shimadzu QP Ultra GC-MS operated in full-scan mode.
The tutorial takes you through steps such as creating a processing method, creating a method to calculate retention indices for features, generating a library of features from a sequence of samples and searching the NIST library for putative identification of unknown compounds. Additionally, the tutorial examines post-processing multivariate and univariate analysis such as principal component analysis, one-way analysis of variance and calculating fold change to help you mine your metabolomics data.
The Frog data tutorial can be downloaded as a PDF and the data files are available from http://bit.ly/2bHGumn.
You can also watch the tutorial on YouTube