non-target roimcr lc-ms study of the disruptive effects over time of tbt on the lipidomics of daphnia magna

Metabolomic studies of biological samples using statistically designed experiments produce large multivariate datasets which can be arranged in three-way data structures and modelled using bilinear and trilinear factor decomposition methods1. the goal of these studies is the discovery of the hidden sources of data variability to facilitate their biochemical interpretation. in this presentation, the application of the new roimcr method2 is shown as a means to recover the maximum number of lipids in non-target lc-ms studies of the disruptive effects over time of tbt on daphia magna3. results of the roimcr method allowed the resolution of a large number of distinct lipid profiles (elution and spectra profiles) whose concentration changes are associated with the different time phases of d. magna intermolt development and with tbt dose. results of the comparison of the results obtained in the non-target analysis with those previously obtained in the target analysis of the same samples are given3. whereas most of the lipids were found in both studies, the non-target analysis provided a larger number of lipids showing statistically significant changes in their concentration due to tbt exposure and time, some of them could be de novo identified, and others were not identified using current databases. the relationship between the effects of the experimental design factors, the interaction between these factors, the structure of the generated three-way datasets and their more appropriate modelling (bilinear or trilinear) are investigated.