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Human sperm swimming in a high viscosity mucus analogue

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalJournal of Theoretical Biology
Volume446
Early online date17 Feb 2018
DOIs
DateAccepted/In press - 13 Feb 2018
DateE-pub ahead of print - 17 Feb 2018
DatePublished (current) - 7 Jun 2018

Abstract

Remarkably, mammalian sperm maintain a substantive proportion of their progressive swimming speed within highly viscous fluids, including those of the female reproductive tract. Here, we analyse the digital microscopy of a human sperm swimming in a highly viscous, weakly elastic mucus analogue. We exploit principal component analysis to simplify its flagellar beat pattern, from which boundary element calculations are used to determine the time-dependent flow field around the sperm cell. The sperm flow field is further approximated in terms of regularised point forces, and estimates of the mechanical power consumption are determined, for comparison with analogous low viscosity media studies. This highlights extensive differences in the structure of the flows surrounding human sperm in different media, indicating how the cell-cell and cell-boundary hydrodynamic interactions significantly differ with the physical microenvironment. The regularised point force decomposition also provides cell-level information that may ultimately be incorporated into sperm population models. We further observe indications that the core feature in explaining the effectiveness of sperm swimming in high viscosity media is the loss of cell yawing, which is related with a greater density of regularised point force singularities along the axis of symmetry of the flagellar beat to represent the flow field. In turn this implicates a reduction of the wavelength of the distal beat pattern — and hence dynamical wavelength selection of the flagellar beat — as the dominant feature governing the effectiveness of sperm swimming in highly viscous media.

    Research areas

  • Sperm motility, Principal component analysis, Low-Reynolds-number flow, Boundary element method

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via Elsevier at https://doi.org/10.1016/j.jtbi.2018.02.013 . Please refer to any applicable terms of use of the publisher.

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    Licence: CC BY

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