Titre
Molecular Imaging with Aquaporin-Based Reporter Genes: Quantitative Considerations from Monte Carlo Diffusion Simulations.
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Chowdhury, R.
Auteure/Auteur
Wan, J.
Auteure/Auteur
Gardier, R.
Auteure/Auteur
Rafael-Patino, J.
Auteure/Auteur
Thiran, J.P.
Auteure/Auteur
Gibou, F.
Auteure/Auteur
Mukherjee, A.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
2161-5063
Statut éditorial
Publié
Date de publication
2023-10-20
Volume
12
Numéro
10
Première page
3041
Dernière page/numéro d’article
3049
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
Publication Status: ppublish
Publication Status: ppublish
Résumé
Aquaporins provide a unique approach for imaging genetic activity in deep tissues by increasing the rate of cellular water diffusion, which generates a magnetic resonance contrast. However, distinguishing aquaporin signals from the tissue background is challenging because water diffusion is influenced by structural factors, such as cell size and packing density. Here, we developed a Monte Carlo model to analyze how cell radius and intracellular volume fraction quantitatively affect aquaporin signals. We demonstrated that a differential imaging approach based on subtracting signals at two diffusion times can improve specificity by unambiguously isolating aquaporin signals from the tissue background. We further used Monte Carlo simulations to analyze the connection between diffusivity and the percentage of cells engineered to express aquaporin and established a mapping that accurately determined the volume fraction of aquaporin-expressing cells in mixed populations. The quantitative framework developed in this study will enable a broad range of applications in biomedical synthetic biology, requiring the use of aquaporins to noninvasively monitor the location and function of genetically engineered devices in live animals.
PID Serval
serval:BIB_6E1FF59417D8
PMID
Date de création
2023-10-06T12:49:22.937Z
Date de création dans IRIS
2025-05-20T21:57:51Z