The University of Southampton
University of Southampton Institutional Repository

A Bayesian approach to characterize fold change detection in Dictyostelium Discoideum

A Bayesian approach to characterize fold change detection in Dictyostelium Discoideum
A Bayesian approach to characterize fold change detection in Dictyostelium Discoideum
The survivability of Dictyostelium cells is highly dependent on how cells sense and response to cyclic-AMP chemoattractant. A key factor in the sense-response mechanism is a feature called 'fold change detection' (FCD), where cells response to the fold changes in stimulus as opposed to its absolute values. Studies have proposed models of the signalling pathway for the sense-response mechanism and skeletal network motifs that exhibit FCD. However, FCD properties in models of sense-response mechanism compatible with experiments that exhibit FCD are poorly understood. In this thesis, we characterize the properties of FCD of Dictyostelium cells by using a mathematical model of experiments that incorporates biochemical variables of the signalling pathway. We created a population of virtual cells by estimating posterior distributions of the model parameters using a Bayesian method. We studied the responses of the virtual cells to various fold changes in stimulus and found that the population of cells is more consistent in sensing lower fold changes. By computing the overlapping areas of distribution of responses we found that the population of cells can distinguish lower fold changes better than higher fold changes. We propose a hyperbolic equation to describe the stimulus-response relation with a logarithmic relation to characterize the uncertainties of the stimulus. We inferred the posterior probability of detecting fold changes using Bayes' theorem and introduce a novel model of prior probability of fold changes. We found that the chances of detecting lower fold changes is higher and posteriors are biased strongly by the conditional probability. To derive the population of cells' perception of fold change, a Bayesian Observer model is constructed and evaluated. It is found that the population of cells perceive uncertainties of lower fold changes better than higher fold changes. There is also a stark difference between perceptions derived from priors modelled from chemotaxis experiment and priors from known families of distribution. We quantified the biases in the perceptions and discovered that biases are more prominent in higher fold changes. The fold distinguishability threshold is also evaluated and its relation with the perceptual bias examined. Our work shows that the characterization of FCD in models of sense-response mechanism can derive theoretical insights not seen in experiments and impose constraints for model selection.
University of Southampton
Kassim, Muhammad Shahreeza Safiruz
ca0fc774-05ef-4444-a723-ff47a425a582
Kassim, Muhammad Shahreeza Safiruz
ca0fc774-05ef-4444-a723-ff47a425a582
Dasmahapatra, Srinandan
eb5fd76f-4335-4ae9-a88a-20b9e2b3f698

Kassim, Muhammad Shahreeza Safiruz (2018) A Bayesian approach to characterize fold change detection in Dictyostelium Discoideum. University of Southampton, Doctoral Thesis, 162pp.

Record type: Thesis (Doctoral)

Abstract

The survivability of Dictyostelium cells is highly dependent on how cells sense and response to cyclic-AMP chemoattractant. A key factor in the sense-response mechanism is a feature called 'fold change detection' (FCD), where cells response to the fold changes in stimulus as opposed to its absolute values. Studies have proposed models of the signalling pathway for the sense-response mechanism and skeletal network motifs that exhibit FCD. However, FCD properties in models of sense-response mechanism compatible with experiments that exhibit FCD are poorly understood. In this thesis, we characterize the properties of FCD of Dictyostelium cells by using a mathematical model of experiments that incorporates biochemical variables of the signalling pathway. We created a population of virtual cells by estimating posterior distributions of the model parameters using a Bayesian method. We studied the responses of the virtual cells to various fold changes in stimulus and found that the population of cells is more consistent in sensing lower fold changes. By computing the overlapping areas of distribution of responses we found that the population of cells can distinguish lower fold changes better than higher fold changes. We propose a hyperbolic equation to describe the stimulus-response relation with a logarithmic relation to characterize the uncertainties of the stimulus. We inferred the posterior probability of detecting fold changes using Bayes' theorem and introduce a novel model of prior probability of fold changes. We found that the chances of detecting lower fold changes is higher and posteriors are biased strongly by the conditional probability. To derive the population of cells' perception of fold change, a Bayesian Observer model is constructed and evaluated. It is found that the population of cells perceive uncertainties of lower fold changes better than higher fold changes. There is also a stark difference between perceptions derived from priors modelled from chemotaxis experiment and priors from known families of distribution. We quantified the biases in the perceptions and discovered that biases are more prominent in higher fold changes. The fold distinguishability threshold is also evaluated and its relation with the perceptual bias examined. Our work shows that the characterization of FCD in models of sense-response mechanism can derive theoretical insights not seen in experiments and impose constraints for model selection.

Text
Final Thesis eprint - Version of Record
Available under License University of Southampton Thesis Licence.
Download (10MB)

More information

Published date: December 2018

Identifiers

Local EPrints ID: 430409
URI: http://eprints.soton.ac.uk/id/eprint/430409
PURE UUID: 29fcb950-ad18-4703-99ca-1602f27c715a

Catalogue record

Date deposited: 30 Apr 2019 16:30
Last modified: 28 Oct 2019 17:36

Export record

Contributors

Author: Muhammad Shahreeza Safiruz Kassim
Thesis advisor: Srinandan Dasmahapatra

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×