Devising Novel Measures of Ciliary and Flagellar Activity

Lead Research Organisation: University of Exeter
Department Name: Engineering Computer Science and Maths


What is it that we humans share with the humble pond scum? The answer turns out to be our cilia - those tiny versatile hair-like protrusions attached to cells. Cilia (interchangeably called flagella) are inextricably involved in many of life's sensory processes including cellular responses to hormones, the propulsion of sperm, and the swimming of free-living micro-algae in our ponds and gardens [1].

Recent years have seen a surge of interest in the structure and biology of cilia. The question of what constitutes "normal" ciliary function is a pressing and prescient issue for the 1 in 1000 people affected by diseases linked to ciliary dysfunction, which cause kidney cysts, blindness, deafness, infertility and more [2]. Consequently, there is increasing demand for mathematical or quantitative methodologies to provide novel insights to further our understanding of ciliary behaviour. These noisy, active and highly-sensitive organelles also exist out of equilibrium - an added complexity that renders them more interesting systems to model and analyse.

Motivated by the discovery that algal flagella exhibit correlated fluctuations reminiscent of human heartbeat dynamics [3], this project will begin by investigating how flagellar beating in a model green alga is modified by environmental perturbations or mutagenesis. The emphasis will be on extracting maximal spatiotemporal information from high-speed live imaging data, and making novel use of fluid mechanics, elasticity, geometry and dynamical systems theory to elucidate any resulting changes to the beating dynamics. One key aim is to harness the power of mathematics to identify, interpret, and model the observed morphological variability, and thereby contribute to developing a novel diagnostic platform to discriminate between normal and pathological modes of ciliary/flagellar beating. This will be tested on algal flagella in the first instance, and if successful, provide a robust and reliable measure of abnormal ciliary activity that will ultimately be made applicable to mammalian ciliopathies.

The EPRSC-DTP funded student will be based in Exeter's brand new interdisciplinary Living Systems Institute, and will have a unique and exciting opportunity to engage in cutting-edge research and collaborations that go beyond traditional subject boundaries. The student is expected to develop and participate in experimental work that will complement the theoretical aspects of this project.

[1] K.Y. Wan & R.E. Goldstein (2016), Coordinated beating of algal flagella is mediated by basal coupling, Proc. Nat. Acad. Sci. USA (113) E2784-93
[2] I. Ibanez-Tallon, N. Heintz, H. Omran (2003), To beat or not to beat: roles of cilia in development and disease, Hum. Mol. Gen. (12) R27-35
[3] K.Y. Wan & R.E. Goldstein (2014), Rhythmicity, recurrence, and recovery of flagellar beating, Phys. Rev. Lett. (113) 238103


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509656/1 01/10/2016 30/09/2021
1927492 Studentship EP/N509656/1 01/10/2017 31/10/2021 Naomi Kennedy
EP/R513210/1 01/10/2018 30/09/2023
1927492 Studentship EP/R513210/1 01/10/2017 31/10/2021 Naomi Kennedy
Description I am in the process of developing an automated computer algorithm, that should be able to diagnose mutations that affect flagella. The alga Chlamydomonas reinhardtii is the subject of this algorithm. I am now able to use this algorithm to measure the curvature and tangent angles on the flagella, and how they propagate along a flagellum with time. Although the results I currently have are merely preliminary and I have only so far looked at two strains, these two variables look promising as a diagnostic tool. I am working on a way for measured forces to be used in a similar manner, but this aspect of the algorithm is not yet viable. Another tool I have developed compares the period of a beat cycle and the area covered by the flagella over the said beat cycle. Plotting these two variables on a graph, with each data point representing one beat cycle, each strain I have worked with has its own distinct cluster.
Exploitation Route The subject of my study is an alga called Chlamydomonas reinhardtii, and specifically what are called flagella, which are cellular appendages they use to swim. Many human cells have the same structure, where they are more commonly called cilia and serve a variety of functions. For example, in your trachea, they clear away the mucus; in the Fallopian tubes, they move the egg cells towards the uterus; sperm cells, like the algae, use them to swim.

The algorithm I am developing, or at least a modified version thereof, could be used by other researchers in my field to analyse any cell that has flagella. In the medical field, it could potentially be used to diagnose diseases such as primary ciliary dyskinesia, which prevents the tracheal cilia from properly clearing away the mucus, with resultant respiratory infections. It might also help diagnose male infertility, or vulnerability to ectopic pregnancy via defective Fallopian cilia.
Sectors Digital/Communication/Information Technologies (including Software),Healthcare

Title Chlamydomonas reinhardtii flagellar tracking algorithm 
Description This is a collection of Matlab programming functions, that between them, can track the two flagella of a Chlamydomonas reinhardtii cell, when it is held stationary by a micropipette. With each still frame from the raw footage, the code converts it into a binary (black-and-white, no grey) image, where the white regions correspond to the locations of the flagella, and the rest is black. Each such white region is discretised into a pre-determined number of points; these points describe a line through the centre of the white region. After polynomial smoothing, these lines are taken as the locations of the flagella at a given instant of time. I also have some other Matlab functions, that can use the measured lines to calculate the forces, curvatures and tangent angles at a given point on the flagellum, at a given time instant. All of my code is a work in progress. 
Type Of Material Computer model/algorithm 
Year Produced 2020 
Provided To Others? No  
Impact This code should enable me to demonstrate differences between strains of Chlamydomonas reinhardtii, in variables like tangent angle, curvature and force generated. This is the next step of my research.