Biodesign researchers identify new way to diagnose urinary tract infections

Biodesign researchers identify new way to diagnose urinary tract infections

August 29, 2019

August 29, 2019

UTI

Three little letters -- U, T and I – conjure up images of pain, bloating, fever and discomfort. According National Institutes of Health, urinary tract infections (UTIs) encompass one quarter of all bacterial infections suffered by humans. Women, in particular, fall prey to UTIs. Global statistics predict that 60% of women have experienced a UTI. The majority will contract this infection before the age of 24, with the expectation of reoccurrences throughout the rest of their lives. The World Health Organization estimates the global cost of office visits and hospitalizations dealing with UTIs to be a staggering $1 billion dollars per year.

Overall, diagnosing and treating a UTI is a tricky business. Cognizant of the need to stop an infection in its tracks, physicians typically initiate an antibiotic prescription upon diagnosis. Untreated UTI infections can lead to complications or hospitalizations, especially in patients with compromised immune systems where it can spread to the kidneys. It can also cause sepsis. According to the National Institutes of Health, severe sepsis initiated from a UTI has a globally accepted mortality rate of 20%.

“Due to the absence of rapid diagnostic tools, physicians often do not have the luxury of fully understanding the underlying cause of a UTI,” said Shelley Haydel, Ph.D, a Biodesign researcher and faculty member in the  ASU School of Life Sciences. “Our work is focused on giving physicians the tools they need. With our new approach, doctors will be able to treat UTIs more effectively and more accurately.” With UTIs often being repeat offenders, a better understanding of the cause is likely to not only decrease the pain and discomfort, but also the overall incidence of the infection.

Since the bacteria, E. coli (Escherichia coli), causes roughly 70% of the UTIs, physicians often base their treatment decision on the assumption that E. coli is responsible for the infection. The remaining 30% of the bacteria are a mixed bag of urethral interlopers. Lab tests to identify the bacteria take between one day and one week to process. A further complication is that existing tests cannot immediately determine if the microbe is antibiotic-resistant. The optimal situation would be a test that could provide a result that, within a few hours, tells which antibiotic to prescribe.

E. coli, alone, has over 100 strains that are known to infect humans—many of which have been unintentionally selected via overprescribing or improperly following prescription instructions. There is an alarming trend of new strains that are completely resistant to even the strongest antibiotics available. Antibiotic resistance allows the bacterial infection to continue to spread and grow stronger even when the patient is taking antibiotics. According to the Centers for Disease Control and Prevention, between 30% and 50% of drugs prescribed are either unnecessary or inappropriate. 

Speeding up the diagnosis from days to hours

Arizona State University researchers are collaborating with Mayo Clinic physicians and Biosensing Instrument Inc. researchers to meet the challenge of improving UTI diagnostics. Armed with a $5.8 million grant from the National Institutes of Health, the team has identified a way to speed up the diagnostic process and identify the specific bacteria, but also detect if the bacteria is susceptible or resistant to antibiotics.

NJ Tao, Ph.D., director of the Biodesign Center for Bioelectronics and Biosensors is the principal investigator. Shaopeng Wang, Ph.D., and Haydel, are project coinvestigators at the center. Thomas Grys, Ph.D., director of microbiology at Mayo Clinic, is responsible for the clinical aspects of the project. Win Ly, Ph.D., research and development director at Biosensing Instrument Inc., is involved with managing the details of creating the prototype. The team, along with the graduate students performing the work, recently published their paper, “Rapid Antimicrobial Susceptibility Testing of Patient Urine Samples Using Large Volume Free-Solution Light Scattering Microscopy” for American Chemical Society’s journal, Analytical Chemistry.

Outpacing the spread of urinary tract infection

“We are using a new visualization technique in which artificial intelligence recognition is combined with volume light scattering microscopy,” said Tao. “Our method not only allows us to instantly recognize the individual cells, but also tests the samples with specific antibiotics to ensure that they are effective.”

The teams have tested their strategy with two common antibiotics: ampicillin and ciprofloxacin. Manni Mo, a doctoral candidate in Biodesign Center for Bioelectronics and Biosensors and the School of Molecular Sciences, tested patient samples while Wang, helped build the instrument’s prototype. Yunze Yang, a postdoctoral scholar at the research center, and others, assisted with the experiments and data analysis.

“We have been able to track the cells in real time, and our technique is proving to be incredibly accurate,” said Mo. “We demonstrated the detection of E. coli in 24 clinical urine samples with 100% sensitivity and 83% specificity.”

“These results are encouraging. Not only is our method working, but it is also simpler,” said Haydel.  “We are using patient samples—that are simply diluted—and do not require several steps of manipulation. This saves an incredible amount of time.”

The work is still in the initial stages, with the team continuing to work to improve the performance of the technology.

“Eventually these methods will be beneficial in determining the activity and effectiveness of newly designed antibiotics,” said Haydel. Using this work as a foundational model, the research team plans to expand the method for several other relevant bacterial infections that affect public health.

“We have used technology to our advantage to offer both simplicity of method and accuracy in diagnosis,” said Tao when relating the success of the project. “Our collaborative effort with end users and instrument developers is key.”

 

Written by: Christine Lewis