Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs
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 (3R...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/24/9/7912 |
| _version_ | 1797602422912188416 |
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| author | Gaël Even Anthony Mouray Nicolas Vandenabeele Sophie Martel Sophie Merlin Ségolène Lebrun-Ruer Magali Chabé Christophe Audebert |
| author_facet | Gaël Even Anthony Mouray Nicolas Vandenabeele Sophie Martel Sophie Merlin Ségolène Lebrun-Ruer Magali Chabé Christophe Audebert |
| author_sort | Gaël Even |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T04:16:52Z |
| format | Article |
| id | doaj.art-20192e1ee6f942ef960016d460968a72 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-11T04:16:52Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-20192e1ee6f942ef960016d460968a722023-11-17T23:02:19ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-04-01249791210.3390/ijms24097912Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental DesignsGaël Even0Anthony Mouray1Nicolas Vandenabeele2Sophie Martel3Sophie Merlin4Ségolène Lebrun-Ruer5Magali Chabé6Christophe Audebert7GD Biotech-Gènes Diffusion, F-59000 Lille, FrancePlateforme d’Expérimentations et de Hautes Technologies Animales, Institut Pasteur de Lille, F-59019 Lille, FrancePlateforme d’Expérimentations et de Hautes Technologies Animales, Institut Pasteur de Lille, F-59019 Lille, FranceGD Biotech-Gènes Diffusion, F-59000 Lille, FranceGD Biotech-Gènes Diffusion, F-59000 Lille, FranceGD Biotech-Gènes Diffusion, F-59000 Lille, FranceCNRS, Inserm, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017-CIIL-Centre d’Infection et d’Immunité de Lille, Université de Lille, F-59000 Lille, FranceGD Biotech-Gènes Diffusion, F-59000 Lille, FranceThe 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.https://www.mdpi.com/1422-0067/24/9/7912animal batchesexperimental designmicrobiota16S metagenomicsalgorithm |
| spellingShingle | Gaël Even Anthony Mouray Nicolas Vandenabeele Sophie Martel Sophie Merlin Ségolène Lebrun-Ruer Magali Chabé Christophe Audebert Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs International Journal of Molecular Sciences animal batches experimental design microbiota 16S metagenomics algorithm |
| title | Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs |
| title_full | Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs |
| title_fullStr | Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs |
| title_full_unstemmed | Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs |
| title_short | Bact-to-Batch: A Microbiota-Based Tool to Determine Optimal Animal Allocation in Experimental Designs |
| title_sort | bact to batch a microbiota based tool to determine optimal animal allocation in experimental designs |
| topic | animal batches experimental design microbiota 16S metagenomics algorithm |
| url | https://www.mdpi.com/1422-0067/24/9/7912 |
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