Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease

Kilian, C.; Ulrich, H.; Zouboulis, V.; Sprezyna, P.; Schreiber, J.; Landsberger, T.; Büttner, M.; Biton, M.; Villablanca, E. J.; Huber, S.; Adlung, L.

doi:10.1101/2023.10.27.561846

bioRxiv · 10.1101/2023.10.27.561846

Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease

Kilian, C.·Ulrich, H.·Zouboulis, V.·Sprezyna, P.·Schreiber, J.·Landsberger, T.·Büttner, M.·Biton, M.·Villablanca, E. J.·Huber, S.·Adlung, L.

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Abstract

Single-cell mRNA sequencing (scRNA-seq) allows deep molecular and cellular profiling of immunological processes. Longitudinal scRNA-seq datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. Here, we derived longitudinal changes in the abundance of six colonic cell types during inflammatory bowel disease (IBD) from scRNA-seq data of a mouse model of colitis using ODE-based models. We then predicted the immune dynamics of a different mouse colitis protocol and confirmed these scRNA-seq-based predictions with our previously published single-cell-based flow cytometry data. We further 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 model simulations by predicting genes indicative of treatment response in human IBD patients. The predictive power of IBD deterministic modelling from scRNA-seq data highlights its potential to advance our understanding of immune dynamics in health and disease.

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Kilian, C., Ulrich, H., Zouboulis, V., Sprezyna, P., Schreiber, J., Landsberger, T., Büttner, M., Biton, M., Villablanca, E. J., Huber, S., Adlung, L.. 2023-10-30. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. https://doi.org/10.1101/2023.10.27.561846

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