University of Illinois researchers have developed a new technique to determine the fertility of sperm samples in cattle.
“This work is a part of a five-year project to develop dairy cattle that are resistant to heat and diseases in tropical areas. We want to donate these cows to developing countries to increase their food production,” University of Illinois department of animal sciences professor Matthew B. Wheeler said.
In order to develop these traits in cattle, the researchers need to determine which sperm samples work best for in vitro fertilization, the announcement said.
A novel imaging approach, published in the Proceedings of the National Academy of Sciences, moves that effort forward.
“Although males may have sperm that are seemingly perfect, there could be morphological or DNA issues. This approach allows us to evaluate the spermatozoa and select the best in terms of fertility,” said Marcello Rubessa, a research assistant professor on Wheeler’s team.
Traditional techniques for imaging sperm samples are slow, labor intensive and involve toxic stains. To circumvent this issue, Wheeler’s team — along with a group based at the Beckman Institute for Advanced Science & Technology — used label-free imaging techniques developed in the Beckman Institute’s Quantitative Light Imaging Laboratory (QLIL) to determine what parameters of the sperm make them fertile.
“We knew from the fertilization experiments which sperm samples worked. We used our imaging technique to understand what parameters were important for success,” said Mikhail Kandel, a graduate student with QLIL. “We saw that the relationship between the size of the head and the tail of the sperm is an important parameter for fertility.”
Additionally, the researchers also improved the speed of the technique. “We used artificial intelligence to automate the process of analyzing these sperm cells,” Yuchen He, a graduate student with QLIL, said.
The researchers hope to improve the speed of the technique for future analysis. “The motility of the sperm is sometimes fast. Therefore, we need to do the measurements quickly,” said QLIL director Gabriel Popescu, a professor in the University of Illinois department of electrical and computer engineering and department of bioengineering.
“For many years, we have developed various techniques for label-free imaging knowing that we had to give away molecular specificity,” Popescu said. “However, our newly developed phase imaging with computational specificity brings back the molecular specificity via [artificial intelligence], which is harmless and works on live cells. The applications are limitless, but one that truly benefits from absence of chemical stains is assisted reproduction, as described in this collaborative study.”
The researchers hope to further develop the technique for assisted reproductive technology in humans, the announcement noted.
The study was supported by grants from the Ross Foundation, the U.S. Department of Agriculture, the National Institutes of Health and the Integrated Grants Management System.