USC Viterbi School of Engineering Ph.D. student Samantha McBirney's research focuses on better detection methods for two superbugs in catheter-related bloodstream infections. Photo courtesy of USC Viterbi Armani Research Lab
Meet Staphylococcus aureus and Pseudomonas aeruginosa, two of the deadliest bacteria responsible for catheter-related bloodstream infections.
Thanks to the research of Samantha McBirney, a Ph.D. candidate in the USC Viterbi Department of Biomedical Engineering, these aggressive bacteria can now be studied with an optimal method that yields reproducible results—key to a better fundamental understanding of their biology and growth patterns needed to develop effective treatment.
Typically, patients in hospital intensive care units are most susceptible to these infections due to multiple catheter insertion sites that are likely to get infected. In about 25% of patients who acquire these virulent bacterial infections, the result is fatal.
“These two types of bacteria are particularly bad because they are categorized as ‘superbugs’,” said McBirney, a member of the USC Viterbi Armani Research Lab. “They’re resistant to nearly all antimicrobial drugs on the market, and they have this incredible ability to develop new resistance mechanisms as new antimicrobials are created. It’s tough to keep up!”
For that reason, McBirney thought that developing a sensor located at the catheter site would dramatically improve diagnosis and treatment. But the first step in the sensor development was understanding the bacterial growth cycle, and that research, in and of itself, proved a stumbling block.
An Ill-Suited Method
Using a conventional method, an OD 600 spectrophotometer, McBirney found that her research results on bacterial growth were poorly reproducible--and for a surprising reason overlooked for decades.
“The OD 600 relies on the ability of whatever it is you’re trying to detect to scatter orange light, or light that has a wavelength of 600nm,” said USC Viterbi Fluor Early Career Chair and Associate Professor Andrea Armani. “But if the thing you’re trying to detect is approximately 600nm in size, then it’s not going to scatter 600nm light very well. Unfortunately, one of the superbugs (Staphylococcus) falls into that size range.”
Commonly referred to as “Staph,” this superbug has consistently eluded researchers working on effective treatment. In fact, with the OD 600, Staph would not be detectable until the concentration had exceeded a critical threshold in which the spherical-shaped bacteria had started clumping together like frozen peas.
“If you’re detecting a growth cluster of Staph in a patient sample using OD 600, the infection is extremely severe and, often, patients don’t respond to treatment,” explained McBirney.
Pseudomonas is also difficult to detect, but for different reasons. Whereas Staphylococcus clusters and remains static, Pseudomonas is rod-shaped with a long tail and motile, making it completely different in terms of its optical scattering properties.
Thus, McBirney found her research shift toward something seemingly basic – developing a reliable and reproducible way to detect these bacteria in the first place.
“When we began, we did not even recognize that OD 600 reproducibility was a problem,” said Armani. “But the more we investigated, the more we realized that the original rationale for using 600nm wavelength light as the standard no longer held true.”
McBirney and her research advisor, Associate Professor Andrea Armani. Photo courtesy of USC Viterbi Armani Research Lab.
Math to the Rescue
Instead of assuming that the bacterium interacted strongly with 600nm light, Armani and McBirney started their analysis by investigating the scattering behavior of the bacterium over the entire visible wavelength range. In addition, the two generated an algorithm to determine the optimal wavelengths to study the two bacteria.
“Everyone has just been using OD 600 for decades without stopping to consider if it’s truly the best approach,” McBirney said. “Nobody was looking into this.”
Using a UV-Vis spectrophotometer, McBirney acquired data on a 1 mL sample of bacterial growth culture every 15 minutes for 11 hours. The instrument measured how much light the culture scattered from 300nm through 800nm.
For the algorithm, she needed two specific data points – the wavelength at which the bacterium optically scattered the most, and the wavelength at which it scattered the least. Optimal wavelengths known, she could finally observe the change in bacterial growth over time.
“We don’t even really get outliers, the data obtained using our algorithm is so consistent and reproducible. It’s a classic bacterial growth curve,” said McBirney. “And yet, when you look at OD 600 measurements for the two bugs, the plots look more like noise than anything else, with huge error bars.”
A Better Way Forward
Long-term, McBirney hopes the algorithm will be applied to future bacterial research. OD 600 instrumentation is present in most bacteria labs, as is a UV-Vis spectrophotometer, which is what McBirney used for her research.
“We’re hoping this new approach gets adopted by research labs, which should be easy given the instrumentation used is already present in most lab settings,” McBirney said. “The only difference is that researchers would simply be using our algorithm to determine bacterial growth and concentration. Hopefully, this information will allow us to more accurately characterize the growth patterns of bacteria, which will lead to a better understanding of the pathogenesis of infections caused by them. We’ll then be able to start working towards better treatments for these infections and, fingers crossed, cures.”
McBirney’s research, titled “Wavelength normalized spectroscopic analysis of Staphylococcus aureus and Pseudomonas aeruginosa growth rates,” was published in Biomedical Optics Express this past September.