Health, Recognizing Diseases from Body Odor: Mini-sensors for Rapid and Low-Cost Diagnostic Tests

Tiny sensors similar to breathalyzers could recognize bacterial infections and detect antibiotic-resistant pathogens in body fluids, according to a study published in the journal Cell Biomaterials by scientists at ETH Zurich . The team, led by Andreas Guntner, Catherine Jutzeler, Thomas Kessler, Emma Slack, and Adrian Egli, developed an innovative approach to detect diseases through the odor of body fluids. The technology, experts say, could provide rapid and affordable diagnostic tests that could improve treatment plans and help fight antibiotic resistance.

“Our method,” Guntner says, “allows us to bypass laboratory testing, which is often a time-consuming process, and obtain results in minutes or even seconds.” Historically, the authors report, doctors have used their sense of smell to diagnose bacterial infections. Pseudomonas aeruginosa is known to have a sweet odor, while Clostridium is associated with a putrid smell. The odor profile of microorganisms depends on the presence of volatile organic compounds (VOCs), tiny molecules emitted by microbes and other organisms. As part of the investigation, the scientists propose using chemical sensors to detect bacteria-associated VOCs in bodily fluids such as blood, urine, feces, and sputum. “We have already developed and marketed similar systems,” Guntner adds, “to detect contamination in alcoholic beverages. We are trying to transfer this system to more complex situations. The development of sensors for use in clinical practice will require further research, especially because the concentrations of VOCs emitted by bacteria are extremely low and can be quite heterogeneous.”

The sensors, the researchers hypothesize, could be made using materials such as metal oxides, polymers, graphene derivatives and carbon nanotubes. To simplify detection, the devices should also be equipped with filters to remove non-informative compounds. In this sense, artificial intelligence and machine learning algorithms will play a fundamental role in the design of these technologies. “The resulting devices,” Guntner concludes, “will offer a rapid and portable method to diagnose bacterial infections, which could be used without special training. The ultimate goal is to translate scientific advances in VOC analysis into practical and reliable tools, in the hope that this possibility will improve patient health and support antibiotic stewardship.”