On the hunt for mastitis-causing bacteria
Dressed in coveralls and rubber boots, I carefully collect milk samples from the udders of Holstein cows at a dairy farm near Saskatoon, Sask. Besides the 5 a.m. start time, my biggest challenge is preventing the cows from knocking any manure or debris into the tiny test vials.
We’re using these milk samples to learn more about bacteria that cause painful udder infections (mastitis) in dairy cows. Although many different bacteria can cause mastitis, our research team at the Western College of Veterinary Medicine (WCVM) is particularly interested in a group of bacteria called coagulase-negative staphylococci (CNS).
These bacteria generally cause infections that are very hard to detect because the cows show no clinical symptoms. As major pathogens that cause mastitis become better controlled, the prevention of CNS is increasingly critical to dairy farmers.
“Udder health is important to the dairy industry, and when dealing with CNS, prevention is better than treatment,” says Colleen Fitzpatrick, a PhD student whose work is supervised by WCVM dairy specialist Dr. Chris Luby.
“We need to have a good understanding of this group of bacteria so we can learn how to effectively prevent the infections they cause.”
CNS includes more than 50 different species of bacteria. Each of these species has their own characteristics and researchers need to learn about each one to help prevent infections. Of these 50 species, only a handful of bacteria have been studied individually.
That’s where Fitzpatrick’s PhD project is important. She’s studying where each CNS bacteria species lives and which species are most likely to cause mastitis. In addition to milk samples, we take samples of water and bedding.
We also take sample swabs from the cows and other animals such as cats and dogs that come and go from the producers’ dairy barns. Fitzpatrick uses these samples to see if CNS species that cause mastitis also live in other places of the barn.
My part of the project is to look for a relationship between the levels of CNS found in the milk and the corresponding somatic cell count (SCC) level found in the same milk sample.
SCC is the measure of the number of immune cells in the milk — primarily macrophages, lymphocytes and neturophils. SCC levels will increase when there’s an infection present in the udder.
Many dairy farms routinely monitor their milk to help detect cows that have high SCC levels. It’s important to identify these animals because producers are penalized if their bulk tank SCC levels are too high. If producers can detect these cows early, they can treat the animals appropriately and make environmental changes in their barns to decrease the SCC levels in the farm’s bulk tank.
My research project’s goal was to determine how many CNS colonies are needed to increase the SCC levels in the milk.
After analyzing my collection of milk samples, I found that an infection of more than 200 colony forming units (cfu) per millilitre (ml) of CNS caused a significant increase in SCC compared to no CNS. I also found that when the level of infection increased to over 1,000 cfu/ml, the SCC levels were significantly greater than 200 cfu/ml or 0 cfu/ml (zero CNS).
While previous studies have found varied results, my project’s findings indicate that the level of CNS infection does play a role in an individual cow’s SCC levels. It’s important to find out the impact of CNS on the SCC levels found on Saskatchewan dairy farms.
As dairy farmers now understand, cows with a CNS infection can produce less milk and decrease the farm’s overall production and efficiency. If Fitzpatrick and other researchers can learn more about where each CNS species lives and its specific characteristics, producers can adopt effective, on-farm strategies for preventing CNS infections — or even eliminating these bacteria species from their facilities before dairy production is affected.
Amanda Byers of Vanderhoof, B.C., is a second-year veterinary student who participated in the WCVM’s Undergraduate Summer Research and Leadership program in 2013.