†Nanowork NewsMany different types of bacteria and viruses can cause pneumonia, but there is no easy way to determine which microbe is causing a particular patient’s disease. This uncertainty makes it more difficult for doctors to choose effective treatments because the antibiotics commonly used to treat bacterial pneumonia will not help patients with viral pneumonia. In addition, limiting the use of antibiotics is an important step in reducing antibiotic resistance.
MIT researchers have now designed a sensor that can distinguish between viral and bacterial pneumonia infections, which they hope will help doctors choose the right treatment.
“The challenge is that there are many different pathogens that can lead to different types of pneumonia, and even with the most extensive and sophisticated testing, the specific pathogen causing a person’s disease cannot be identified in about half of patients. And if you treat viral pneumonia with antibiotics, you could be contributing to antibiotic resistance, which is a big problem, and the patient won’t get better,” said Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science at MIT and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science.
In a study in mice, the researchers showed that their sensors could accurately distinguish bacterial and viral pneumonia within two hours, using a simple urine test to read the results.
Bhatia is the senior author of the study, which appears in the Proceedings of the National Academy of Sciences †“Host protease activity classifies the etiology of pneumonia”† Melodi Anahtar ’16, PhD ’22 is the lead author of the paper.
Signatures of infection
One of the reasons it’s difficult to differentiate between viral and bacterial pneumonia is that there are so many microbes that can cause pneumonia, including the bacteria Streptococcus pneumoniae and Haemophilus influenzae, and viruses such as influenza and respiratory syncytial virus (RSV).
When designing their sensor, the research team decided to focus on measuring the host’s response to infection, rather than trying to detect the pathogen itself. Viral and bacterial infections trigger different types of immune responses, including the activation of enzymes called proteases, which break down proteins. The MIT team found that the activity pattern of those enzymes may serve as a hallmark of bacterial or viral infection.
The human genome encodes more than 500 proteases, many of which are used by cells that respond to infection, including T cells, neutrophils and natural killer (NK) cells. A team led by Purvesh Khatri, an associate professor of medicine and biomedical data science at Stanford University and one of the authors of the paper, collected 33 publicly available datasets of genes expressed during respiratory infections. By analyzing that data, Khatri was able to identify 39 proteases that seem to respond differently to different types of infections.
Bhatia and her students then used that data to create 20 different sensors that can interact with those proteases. The sensors consist of nanoparticles coated with peptides that can be cleaved by certain proteases. Each peptide is labeled with a reporter molecule that is released when the peptides are cleaved by proteases that are upregulated upon infection. Those reporters are eventually excreted in the urine. The urine can then be analyzed by mass spectrometry to determine which proteases are most active in the lungs.
The researchers tested their sensors in five different mouse models of pneumonia caused by infections from Streptococcus pneumoniae, Klebsiella pneumoniae, Haemophilus influenzae, influenza virus and mouse pneumonia virus.
After reading the results of the urine tests, the researchers used machine learning to analyze the data. Using this approach, they were able to train algorithms that could distinguish between pneumonia and healthy controls, as well as distinguish whether an infection was viral or bacterial, based on those 20 sensors.
The researchers also found that their sensors could distinguish between the five pathogens they tested, but with a lower accuracy than the test used to distinguish between viruses and bacteria. One possibility the researchers could pursue is to develop algorithms that can not only distinguish bacterial from viral infections, but also identify the class of microbes that cause a bacterial infection, which could help doctors choose the best antibiotic to treat. fight that type of bacteria.
The urine-based readout is also amenable to future detection with a paper strip, similar to a pregnancy test, which would allow for a diagnosis at the point of care. To that end, the researchers identified a subset of five sensors that could bring home testing closer. However, more work is needed to determine whether the reduced panel would work equally well in humans, who have more genetic and clinical variability than mice.
In their study, the researchers also identified some patterns of host response to different types of infection. In mice with bacterial infections, neutrophil-secreted proteases were seen more prominently, which was expected because neutrophils tend to respond more to bacterial infections than to viral infections.
Viral infections, on the other hand, triggered protease activity of T cells and NK cells, which are usually more responsive to viral infections. One of the sensors that generated the strongest signal was linked to a protease called granzyme B, which causes programmed cell death. The researchers found that this sensor was highly activated in the lungs of mice with viral infections, and that both NK and T cells were involved in the response.
To deliver the sensors to mice, the researchers injected them directly into the trachea, but they are now developing versions for human use that can be administered with a nebulizer or an inhaler similar to an asthma inhaler. They are also working on a way to detect the results using a breathalyzer instead of a urine test, which could provide even faster results.
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