Experiment Design

General idea of cell metabolomics experiment is very straightforward: (a) cells need to be grown under controlled conditions (with or without treatments), (b) sufficient replication has to be performed; (c) sample preparation has to be done using well defined, standard operating procedures; and (d) measurement has to be accomplished using the best available method with sufficient referencing. Control of the cell growth conditions can be achieved and therefore major confounding factors often threatening accuracy of metabolomics analysis in organism or populations can be avoided. In order to avoid possible technical differences and errors, experimental design must still incorporate randomization, replication and local control in a manner similar to approaches developed for clinical trials.

Randomization protects an experiment against extraneous factors of chance, such as different person performing experiments, variations in the temperature or humidity in the room etc. It is crucial to understand all possible sources of variability and minimize their effects by randomizing the samples accordingly and by introducing quality control standards.

Replication is utilized in order to increase statistical accuracy of the results. It is crucial to include biological replicates and, also if possible, technical replicates. Technical replicates represent different aliquots of a sample or of a batch of samples. Technical replicates show the consistency of the experimentation. Cell culture experiment has to include several repeats of growth and treatment for all explored cell types (biological replicates). The required number of technical and biological replicates depends on the variability between samples, the expected range of variability, variance between observed groups (window of effect) and the power of the test being performed. The number of replicates will therefore need to be determined for each specific experiment from preliminary measurements.

Finally, local control requires that the known sources of variability are either completely removed (if possible) or are deliberately made to fluctuate widely (by collecting many samples with large coverage of difference sources of variability) so that their effects can be measured and eliminated, i.e. averaged out, from experimental error.

A major attention in the cell culture metabolomics experiment should be placed on the selection of culture growth conditions and medium. Cell growth conditions and medium can vary in temperature, gas mixture, pH, glucose concentration, growth factors and presence of other nutrients. Cells density as well as feeding strategy also significantly influences the metabolic profiles. Finally, passage number and cell growth stage can have significant effect as well. Metabolomics can be used to monitor these changes but at the same time, in the design of metabolomics experiment all of these factors have to be considered and controlled.

Recent review dealing with experimental design in metabolomics has been published by Suhre and Gieger (2012). Although most of the focus of the review is on clinical applications of metabolomics, many issues relate directly to cell culture applications as well. Experimental design issues and solutions specific to cell culture metabolomics and applications presented in this chapter are provided in Fig. 20.2.

Fig. 20.2 Major steps in cell culture metabolomics experiments including main issues and possible solutions

 
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