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Details of Grant 

EPSRC Reference: EP/P013651/1
Title: Modelling sperm-mucus interactions across scales
Principal Investigator: Keaveny, Dr E E
Other Investigators:
Degond, Professor PAA
Researcher Co-Investigators:
Project Partners:
Department: Dept of Mathematics
Organisation: Imperial College London
Scheme: Standard Research
Starts: 01 April 2017 Ends: 31 March 2021 Value (£): 694,462
EPSRC Research Topic Classifications:
Biophysics Continuum Mechanics
Numerical Analysis
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
29 Nov 2016 EPSRC Mathematical Sciences Prioritisation Panel November 2016 Announced
Summary on Grant Application Form
The process of the sperm reaching the egg is the reason we are all here, but we often don't stop to think, why was it that particular sperm and not one of the billions of others? If we do, we usually assume that it was all up to chance and that the sperm that provided half of our genetic make up simply had about a one-in-a-billion shot of being the one. This, however, is not the complete story and, as experimental evidence shows, the female tract deploys a variety of biochemical and biophysical mechanisms to actively select the most viable sperm cells, allowing only this group the chance at fertilising the egg. Understanding the mechanisms at play is not only fundamental to our understanding of reproductive biology, but also crucial to effectively diagnosing and treating cases of infertility.

One key player in sperm selection is mucus: the complex fluid through which the sperm cells must swim. When we think of mucus, we often think of a slimy and gooey substance. The gooeyness is due to the fact that mucus in comprised of a network of elastic filaments suspended in water. Due to its small size, a sperm cell, rather than experiencing the gooeyness, instead experiences the network as a series of obstacles with which it must interact as it tries to swim. During fertile periods, the properties of the filament network change to allow healthy, viable sperm to pass, while filtering out the rest. It remains unclear, however, which network properties enable this remarkable differentiation between healthy and abnormal sperm cells. Developing a clear understanding of the underlying mechanics of sperm-filament network interactions could pave the way for the development of new diagnostics, based on synthetic artificial mucus environments, as well as new fertility treatments.

The goal of this project is to use mathematical modelling to quantify these sperm-network interactions and explore how they impact sperm selection. The models we develop will be able to examine how both the shape and swimming characteristics of individual sperm affect its ability to move through networks of different properties, as well as how the interactions affect the motion of multiple sperm and sperm populations at scales close to the female tract itself. To do this, we will develop two kinds of mathematical models. The first model will provide a microscopic description of the coupled motion of the sperm cells and filaments by resolving the details of the fluid flows generated by the swimming sperm, the bending and stretching of the network filaments, and the collisions between the sperm cells and network filaments. This model will allow us to explore in great detail how different network properties affect the motion of individual or small groups of sperm cells with different swimming characteristics and morphologies. The second model will describe the dynamics of sperm populations in the female tract at the longer time and larger length scales not accessible to the first model. This model will be derived using a rigorous coarse-graining methodology to systematically eliminate degrees of freedom from the more detailed model while still ensuring relevant effects are captured consistently. Using this model we can explore en masse sperm selection and link population-level differentiation with details of the sperm-mucus interactions.

We aim for these mathematical models to have the two-fold effect of pushing forward fields associated with applied mathematics such as scientific computing, fluid mechanics, non-linear partial differential equations, and multiscale analysis, but also providing important inroads of using mathematics to impact the biological sciences and medicine. A key aspect of our project is to interface with active fertility clinicians and reproductive biologists and explore with them how our models coupled with their laboratory techniques might be used in the future to enhance clinical data and provide better patient outcomes
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Organisation Website: http://www.imperial.ac.uk