A Comparative Bioinformatic Analysis of Optic Nerve Axon Regeneration Lipidomes Using the Xenopus laevis as a Model System.

Abstract

Lipidomics is a rapidly growing branch of metabolomics that identifies lipid compositions of samples to learn more about disease and identify potential novel therapeutic targets. In the context of ophthalmology, lipidomic research has increased our understanding of optic nerve regeneration. The diversity of experimental designs for lipidomic research and the large datasets generated are two obstacles that must be addressed by bioinformatic tools to perform statistical analysis on lipidomics data. Our study provides an objective comparison of the features in two freely accessible web-based bioinformatics tools, MetaboAnalyst 6.0 and LipidOne 2.3, for analyzing an optic nerve regeneration model lipidome. A publicly available lipidomic dataset of the optic nerve axon regeneration model, Xenopus laevis, was used to compare the analytic capabilities of both tools. Though both tools offered univariate and multivariate analysis methods, MetaboAnalyst 6.0 had advantages in customizable data processing, normalization, analysis, and image generation. It also offered consistent multiple-comparison testing correction and comprehensive results/dataset export. Meanwhile LipidOne 2.3 uniquely allowed for univariate and multivariate analysis of lipid classes and lipid building blocks.