Signalling pathways of leukocyte migration in silico.

A mathematical model has the potential of powerful computer (in silico) studies. This is important in the daily lab work when planning new experiments. Indeed, most experiments can be first done in silico and then performed on real animal model after an optimization of the wet experiment outcome. Bearing this in mind, the computer model serves as a platform to reduce the cost of the experiments and the unnecessary sacrifice of animals or human specimens. In addition, the mathematical model provides an alternative approach to wet lab experiments and it links findings from in vitro, in vivo and ex vivo studies together into a whole system.

In this project I will investigate the migration process of macrophages and neutrophils, which are the first layer of defence of the immune system in humans. After an injury, parts of the immune system are activated, specific immune cell leave the blood vessels and migrate through the tissue to the side of the injury. Which signals drive theses immune cells towards the injury, how the cells migrate and what do the cells do once they reached the site of injury are open questions.

To answer these questions I will use data collected in zebrafish, which is a well-established animal model to study the innate immune system. In particular, I will develop data processing algorithms and analysis tools to investigate cell migration tracks.
Furthermore I will study the processes that appear inside these immune cells during the immune response. I will analyse already collected knowledge about separate components of these processes to build an overall network. This analysis will be a guide to construct a mathematical description of the first immune response.

While the major part of this project focuses on the immune system in zebrafish, I will extrapolate the analysis results to mouse and human. This will be achieved by a comparison of pathway, so called pathway mapping.

The aim of this project is to develop zebrafish as an in silico system to study the dynamical processes of the innate immune response. The transparent skin of zebrafish embryos made it an ideal model organism to investigate cell migration processes using fluorescent time-lapse microscopy. The innate immune system of zebrafish embryos closely assembles that of humans and is at early stages clearly separable from the adaptive response.

Many different data types, such as cell migration imaging data or transcriptomics data, have been collected over the past years. However, the full potential of such data has not been explored so far.

I will perform a detailed network analysis of immune cell signalling pathways in zebrafish. The constructed network will be used to generate an improved model of macrophage and neutrophil migration during acute injury. In particular, the cell dynamics will be described by an agent-based hybrid model, which will capture the internal cellular signalling process of each individual cell, as well as the migration process inside the extracellular matrix.

Most cell migration data have been analysed using simple statistics, e.g. the velocity of a cell or the straightness index of a cell. Such statistics fail to describe the detailed migration process. I will further develop random walk models and analysis tools to identify migration patterns in 2D, but even more important in 3D. The developed algorithms will provide powerful tools to study migration processes.

The analysis of leukocyte migration in 3D will be the basis to develop a 3 dimensional in silico model of the innate immune response in zebrafish. This model will be extended to the whole organism level.

The during this proposed project developed image processing algorithms and data analysis tools are not only applicable to the specific system of macrophage and neutrophil migration during innate immune processes. They find fast application in other cell migration studies, such as cancer cell migration, bacterial chemotaxis or even animal movement. This project will help to improve the technologies and optimise the workflow in these areas (impact within 1-2 years).

One of the direct outputs of this research proposal is an implemented computer model describing innate immune response dynamics, which will allow researchers to perform initial in silico drug tests. This is of major interest in clinical studies and in the pharmaceutical industry (impact 1 - 3 years).

The bioinformatics resources will help to guide future research and help to put new experimental results better into context. In silico studies in general will improve the laboratory and clinical work, because an established model of a given process is the basis for most experimental design algorithms. In this way experimental costs will be reduced, which in turn leads to a more efficient usage of resources and public funds (impact 1 - 3 years).

Other very important aspects are animal experiments and clinical trials. The model developed here will provide a platform to exclude uninformative experiment based on in silico analysis. This in turn reduces the amount of necessary animal experiments in a study. In a clinical trial in silico prediction experiments can be used to reduce the risk for the test person (impact 2-5 years).

The principal of performing powerful in silico studies, such as simulation studies under so far not investigated conditions, will lead to a restructuring of the work protocols (impact 3 - 10 years).