Introduction: In animals, the process of fertilization requires that a motile sperm interact with an egg. In most sperm, including those of insects, the motility apparatus is a eukaryotic flagellum and its regulation results from a series of tightly regulated molecular events. The flagellum is a biological nano-machine that is widely conserved through evolution. In recent studies using the mosquito Culex quinquefasciatus, Thaler et. al. (2013) observed a series of three flagellar waveforms that progressed from activation to full progressive motility. This same activation pattern occurred in sperm from a related species, Culex pipiens. The three distinct waveforms observed in vitro were: a low amplitude, low velocity, and high frequency waveform (A), a high amplitude, high velocity, and low frequency waveform (C), and a low velocity intermediate waveform that had superimposed features from both waveforms A and C (B). Based on these findings, we are interested in identifying the molecular switch responsible for the waveform transitions during sperm motility in C. pipiens. Here, we report our studies on C. pipiens with the aim of modeling the mosquito sperm flagellum as a nano-machine.
Materials and Methods: Mosquitoes were euthanized by placing them in a chamber containing a piece of cotton soaked in chloroform. Seminal vesicles and accessory glands were removed while in PBS solution. They were then placed on a glass slide with a drop of insect Ringer’s solution and a coverslip. In some cases, only the seminal vesicles were used. Pressure was applied to the coverslip to break open accessory glands thereby activating sperm. Data was acquired with a Nikon Labphot Microscope at 10x magnification using phase contrast optics and a DAGE-MTI CCD 100 camera. Images were captured using Scion Image and processed using ImageJ to quantify wave parameters.
Results and Discussion: Using phase contrast microscopy and image processing methodologies we obtained parameters for flagellar wavelength and amplitude as well as progressive velocity for sperm displaying waveforms A and C. In addition, we were able to determine the beat frequency for waveform C as well as the dimensions of the sperm head and tail. Once all the desired parameters have been measured with a large sample size, average parameters for each waveform, A and C, will be used to test current physical models. This will provide insight into the development of a mathematical model for this system that will describe the regulation of flagellar motion in both two- and three-dimensions.
Conclusion: The results for the parameters describing waveforms A and C provide confidence in obtaining values that are accurate in order to develop a mathematical model for sperm motility. The model can then be combined with molecular events that occur during motility in order to provide a deeper understanding of flagellar motion. The eukaryotic flagellum serves as an example of a naturally occurring cellular motor and with a better understanding of the mechanism, can aid in the design of nano-scale biomimetic devices.