Bio-informatics framework to study molecular and cellular similarity between 3D cell cultures and tissues
Authors/Creators
- Bah Thierno Sidy1
- Jeanneret Florian1
- Bazelle Pauline1
- Quintard Clément2
- Tubbs Emily1
- Jonsson Gustav3
- Jiao Jie4
- Wang Jun4
- Werschler Nicolas4
- Laporte Camille1
- Pitaval Amandine1
- Pomeranz Gideon5
- Bissardon Caroline1
- Kaal Joris1
- Leopoldi alexandra3
- Hagelkruys Astrid3
- Long David A6
- Blandin Pierre1
- Achard Jean-Luc6
- Navarro Fabrice1
- Fouillet Yves1
- Penninger Josef M7
- Gidrol Xavier1
-
Battail Christophe1
- 1. CEA
- 2. CEA - University of British Columbia
- 3. Institute of Molecular Biotechnology of the Austrian Academy of Sciences
- 4. University of British Columbia
- 5. UCL Great Ormond Street Institute of Child Health
- 6. Grenoble INP
- 7. University of British Columbia - Institute of Molecular Biotechnology of the Austrian Academy of Sciences
Description
In recent years, 3D cell cultures (organoids and tumor spheroids) has generated great interest in biological engineering because they seem to allow a better representation of biological complexity than monolayer cell cultures. However, few works have yet focused on the detailed analysis of the levels of molecular and cellular similarity between different 3D culture models and with the corresponding reference tissues.
We have developed a bioinformatics framework to facilitate the advanced analysis of transcriptomes from multiple experimental conditions of 3D cell cultures. We have setup a strategy to generate controlled cell mixtures from single cell RNA-seq data of reference tissues and to use them to assess the biological complexity of 3D cell cultures.
We applied our approach to analyze the transcriptomes of blood vessel organoids and we were able to identify the experimental conditions allowing to better recapitulate the biology of the reference tissue.
Files
Bah_ECCB-ISMB2023.pdf
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