Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease.
Journal
NPJ systems biology and applications
ISSN: 2056-7189
Titre abrégé: NPJ Syst Biol Appl
Pays: England
ID NLM: 101677786
Informations de publication
Date de publication:
24 Jun 2024
24 Jun 2024
Historique:
received:
21
12
2023
accepted:
14
06
2024
medline:
25
6
2024
pubmed:
25
6
2024
entrez:
24
6
2024
Statut:
epublish
Résumé
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
Identifiants
pubmed: 38914538
doi: 10.1038/s41540-024-00395-9
pii: 10.1038/s41540-024-00395-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
69Subventions
Organisme : Klaus Tschira Stiftung (Klaus Tschira Foundation)
ID : KT46
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 528292361
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 493624519
Informations de copyright
© 2024. The Author(s).
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