Stochastic modelling of intra-cellular bacterial infections
Lead Research Organisation:
University of Leeds
Department Name: Applied Mathematics
Abstract
This project will support an existing collaborative relationship between Dstl and University of Leeds. The aim of the collaboration is to develop mechanistic mathematical models and computational tools that can be used to support experimentalists in the development of medical countermeasures to treat the diseases that may potentially be caused by biological warfare agents.
The aim of this PhD studentship is to make use of experimental work, mathematical models and statistical methods to characterise and better understand FT infection after bacterial escape from the lung. The specific objectives of the project are:
1. Understand disease progression
2. Understand the role of cytokines in the progression of disease; 3. Understand the role of macrophages and neutrophils in the progression of disease, and 4. Develop a mathematical model that includes cytokines, macrophages and neutrophils
The underlying challenge is to develop a quantitative approach to within-host infectious disease progression that (i) integrates a wide range of biological and immunological data, and (ii) increases our understanding of the mechanisms at molecular, cellular and population levels that are exploited by bacteria to avoid alerting the innate or the adaptive immune system.
This work supports the "three R" objectives shared by government, industry and academia: the reduction, refinement and replacement of animals in experimentation, by seeking mathematical and computational approaches as an adjunct or alternative to animal experiments.
The aim of this PhD studentship is to make use of experimental work, mathematical models and statistical methods to characterise and better understand FT infection after bacterial escape from the lung. The specific objectives of the project are:
1. Understand disease progression
2. Understand the role of cytokines in the progression of disease; 3. Understand the role of macrophages and neutrophils in the progression of disease, and 4. Develop a mathematical model that includes cytokines, macrophages and neutrophils
The underlying challenge is to develop a quantitative approach to within-host infectious disease progression that (i) integrates a wide range of biological and immunological data, and (ii) increases our understanding of the mechanisms at molecular, cellular and population levels that are exploited by bacteria to avoid alerting the innate or the adaptive immune system.
This work supports the "three R" objectives shared by government, industry and academia: the reduction, refinement and replacement of animals in experimentation, by seeking mathematical and computational approaches as an adjunct or alternative to animal experiments.
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509243/1 | 01/10/2015 | 31/12/2021 | |||
| 1668051 | Studentship | EP/N509243/1 | 01/10/2015 | 30/09/2019 | Remus Stana |
| Description | We have found how to model the mean time for a molecule to start a immune reaction to a infection (We have modeled other first passage properties of molecules). The model I worked on dealt with molecules produced in an intracellular compartment of a cell which diffuse until they reach the cellular membrane. Depending on the type of molecule, they might also diffuse on the surface of the cell until either a certain period of time has passed or the molecule encounters a ligand. After either of these events the molecules re-enter the cytoplasm and diffuse until they are absorbed by the intracellular compartment. Of particular importance is the average mean time for a molecule to return to the intracellular compartment give that it hit the cellular membrane and for this purpose, I used differential equations, like the Laplace equation, and Green's function method, in bipolar and bispherical coordinates, to model the Brownian motion of the molecule. Additionally, we create a mathematical model for a specific type of assay experiments where Coxiella burnetii bacteria are placed inside a well and are allowed to be phagocytosed by a monolayer of monocytes on the bottom of the well. We obtain an expression for the intracellular bacterial load at any point during the experiment. |
| Exploitation Route | My finding might be used with data from biological studies to estimate parameters of the model. For example, data exists for STAT molecule diffusion and it can be used together with my model to obtain predictions. |
| Sectors | Agriculture, Food and Drink,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
| Title | Assay simulation |
| Description | Given that this project is supporting an existing collaborative relationship between DSTL (Defence Science and Technology Laboratory) and University of Leeds my work also involved constructing a computer algorithm to simulate assay experiments performed by DSTL. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Impact | There have not been any notable impact yet resulting from the use of this software. |
| Description | Presentation to the British Society for Immunology: Mathematical Modelling group meeting in Cambridge 2018 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | I presented my work on modelling intracellular dynamics using stochastic process to the British Society for Immunology: Mathematical Modelling group meeting in Cambridge and I recieved valuable feedback which helped me improve my research. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://www1.maths.leeds.ac.uk/applied/BSI/ |