Vassilis Pachnis & Reimer Kühn

*Video coming soon*

Modelling of cell differentiation in the enteric nervous system

Joint Crick/King's College London position

Neuronal ensembles of the brain and spinal cord are often organised according to spatial and topographic rules which are established during development and ultimately dictate connectivity and function of neural circuits. In contrast to the central nervous system the peripheral nervous system originates from neural crest cells which disperse throughout the body giving rise to networks without obvious spatial or topographic organisation. As a consequence, the rules that control the assembly and organization of peripheral neural circuits remain obscure. The enteric nervous system (ENS) encompasses the intrinsic neural networks of the gut wall which regulate virtually every aspect of gastrointestinal physiology. They also constitute a critical relay station along the microbiota-gut-brain communication axis and are essential for energy balance and homeostasis.

The ENS includes a vast number of neurons (5x108 in humans) and glial cells which are organized into a mosaic of many different subtypes arranged at multiple layers of the gut wall. Despite some recent progress, the principles underlying the assembly of intestinal neural circuits and how organized activity emerges in defiance of the chaotic distribution of enteric neurons and glia remain unclear. To provide insight into these processes we have been characterising the molecular profile of ENS progenitors at multiple stages of mouse embryogenesis using single cell RNA sequencing and gene expression analysis. Here we will use network models and simulations to describe the developmental progression of ENS progenitors along identifiable differentiation trajectories. Our aims are to:

1)    Describe distinct cellular states and define molecular changes associated with cellular transitions.

2)    Understand how key genes and molecular players interact over time to form functional gene regulatory networks.

We will use marker gene expression analysis and transcriptomics of single cells (single cell RNA sequencing) to parameterise a network model. This experimental data will be collected at different time points of the developmental process and the resulting data series will form the numeric basis of a time-dependent Bayes network that will allow us to explicitly model the time domain. Single cell transcriptomics data provide an unprecedented amount of detailed gene expression levels. Preliminary analyses show that about 100 single cells per time point are sufficient to characterise the heterogeneous population of neural progenitor cells, particularly in regard to the expression of known marker gene modules that are used to characterise particular ENS cell lineages.

In addition to encapsulating the observed experimental results, we expect the network models will identify novel marker genes and provide a comprehensive picture of the dynamic transcriptional profiles associated with enteric neurogenesis. One of the most interesting and useful aspect of quantitative theoretical models is their ability to provide predictions. We plan to simulate disease conditions in which critical components of gene network modules are modified, and predict the differentiation of the cellular lineages, or the phenotypic changes of the entire cellular population as a whole. These predictions will then be validated with wet lab experiments on ENS cell populations either in vivo or in vitro. In particular, established disease models can be tested through this combination of theoretical and experimental studies.

1. Lasrado, R., Boesmans, W., Kleinjung, J., Pin, C., Bell, D., Bhaw, L., McCallum, S., Zong, H., Luo, L., Clevers, H., Vanden Berghe, P. and Pachnis, V. (2017)
Lineage-dependent spatial and functional organization of the mammalian enteric nervous system.
Science  356: 722-726. PubMed abstract

2. Konstantinidou, C., Taraviras, S. and Pachnis, V. (2016)
Geminin prevents DNA damage in vagal neural crest cells to ensure normal enteric neurogenesis.
BMC Biology  14: 94. PubMed abstract

3. Heanue, T. A. and Pachnis, V. (2007)
Enteric nervous system development and Hirschsprung's disease: advances in genetic and stem cell studies.
Nature Reviews Neuroscience  8: 466-679. PubMed abstract

4. Hannam, R., Annibale, A. and Kühn, R. (2016)
Preprint: Cell reprogramming modelled as transitions in a hierarchy of cell cycles.
Available at: arXiv. https://arxiv.org/abs/1612.08064

5. Nodelman, U., Shelton, C. and Koller, D. (2003)
Learning continuous time Bayesian networks
Proceedings of the Nineteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03), Acapulco, Mexico, August 7-10 2003. Meek, C. and Kjærulff, U., Eds. San Francisco, Calif., Morgan Kaufmann: 451-458.
Available at: https://dslpitt.org/uai/displayArticleDetails.jsp?mmnu=1&smnu=2&article_id=961&proceeding_id=19