The basis of any animal experimentation begins with the housing of animals that should take into account the need for splitting animals into similar groups. Even if it is generally recommended to use the minimum number of animals necessary to obtain reliable and statistically significant results (3Rs rule), the allocation of animals is currently mostly based on randomness. Since variability in gut microbiota is an important confounding factor in animal experiments, the main objective of this study was to develop a new approach based on 16S rRNA gene sequencing analysis of the gut microbiota of animals participating in an experiment, in order to correctly assign the animals across batches. For this purpose, a pilot study was performed on 20 mouse faecal samples with the aim of establishing two groups of 10 mice as similar as possible in terms of their faecal microbiota fingerprinting assuming that this approach limits future analytical bias and ensures reproducibility. The suggested approach was challenged with previously published data from a third-party study. This new method allows to embrace the unavoidable microbiota variability between animals in order to limit artefacts and to provide an additional assurance for the reproducibility of animal experiments.
Keywords: 16S metagenomics; algorithm; animal batches; experimental design; microbiota.