207 7 General Discussion are derived from the same patient. This heterogeneity between organoids highlights the need for standardized procedures and protocols32. This is particularly important in the field of metabolism which requires precise quantitation. In order to avoid data misinterpretation, correct analysis and interpretation are crucial. In some cases, it may be considered to normalize the data of each individual organoid line to its own control prior to processing with the other biological replicates. This approach could help identify trends in responses to different treatments or as a result of different insults. A second approach to this issue is the use of distribution profiles of individual organoids instead of averages. In that instance, observational studies of each organoid in the culture could help reduce the risk of losing individual responses based on the averaged trend. One example on how to prevent this, is illustrated in chapter 3. OrganelX is able to track individual organoids in time, allowing us to get individual growth rates of all the organoids in a culture. The data for each individual organoid can be used to obtain an average response but also allows to identify individual responses. While this approach could help optimize the interpretation of data, it does not prevent the above-mention heterogeneity. Another limitation of the organoid work is the number of cells and biomass obtained for downstream assays. While organoids are composed of thousands of cells, traditional organoid work is done in 24-well plates containing 50 µldomes. Upon collection, the average number of cells obtained from a 50 µl dome containing hepatic organoids can range from 3·104 to 5·105 cells. In contrast, the average number of HEPG2 cells in a 10 cm2 dish used for metabolic assays ranges between 4·106 and 8·106. While two domes of 50 µL can provide enough material to perform qPCR or immunofluorescence, this would not be sufficient for most metabolic assays. For some metabolic techniques performed in this thesis, pooling of 3-4 wells was required, which in some cases still did not yield enough material for reliable quantification. Moreover, the high number of organoids needed also increased the costs of the experiment. One straightforward approach is to increase the number of organoids, and therefore cells, by upscaling the cultures or optimizing the culture procedures33. This would allow us to obtain more reliable readouts that depend on cell number. However, this can also increase costs associated with the amount of media needed, cytokines and consumables. An alternative solution is to increase the sensitivity of the bioanalytical assays performed in metabolomic studies. Several groups are focused on the profiling of different metabolites in small quantities using small numbers of cells with microscale analytical
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