Virus and Bacterial pneumonia can be distinguished by a nanoparticle sensor.

Pneumonia can be caused by a variety of bacteria and viruses, but there is no straightforward method to tell which organism is causing a patient’s disease. Because the drugs frequently used to treat bacterial pneumonia won’t help individuals with viral pneumonia, this ambiguity makes it more difficult for clinicians to identify appropriate treatments. Furthermore, reducing antibiotic use is an essential step in combating antibiotic resistance.

Researchers at MIT have developed a sensor that can distinguish between viral and bacterial pneumonia infections, which they hope may aid clinicians in selecting the best treatment option.

The problem is that there are many different microorganisms that can cause different types of pneumonia, and even with the most thorough and comprehensive testing, the pathogen causing a patient’s sickness cannot be identified in around half of the cases. 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 say that 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.

The researchers demonstrated that their sensors could reliably differentiate bacterial and viral pneumonia in mice within two hours using a simple urine test.

Bhatia is the study’s senior author, and it was published in the Proceedings of the National Academy of Sciences this week. The paper’s principal author is Melodi Anahtar ’16, Ph.D. ’22.

Infection signatures

Because there are so many germs that can cause pneumonia, including bacteria like Streptococcus pneumonia and Haemophilus influenza, as well as viruses like influenza and respiratory syncytial virus, it’s been difficult to distinguish between viral and bacterial pneumonia (RSV).

The researchers decided to focus on assessing the host’s response to infection rather than trying to detect the pathogen itself when building their sensor. Infections caused by viruses and bacteria elicit different immunological responses, including the activation of proteases, which break down proteins. The MIT researchers discovered that the pattern of activity of those enzymes can be used as a bacterial or viral infection hallmark.

More than 500 proteases are encoded in the human genome, with many of them being employed by cells that respond to infection, such as T cells, neutrophils, and natural killer (NK) cells. Purvesh Khatri, an associate professor of medicine and biomedical data science at Stanford University and one of the paper’s authors, headed a group that gathered 33 publicly available datasets of genes expressed during respiratory infections. Khatri was able to discover 39 proteases that appear to respond differently to different forms of infection after evaluating the data.

The data was then used by Bhatia and her students to construct 20 distinct sensors that can interact with the proteases. Nanoparticles coated with peptides that can be cleaved by specific proteases make up the sensors. A reporter molecule is attached to each peptide, which is released when the peptides are broken by proteases that are increased during infection. Eventually, those reporters are eliminated in the urine. After that, mass spectrometry can be used to determine which proteases are most active in the lungs.

The researchers put their sensors to the test in five distinct mouse pneumonia models generated by Streptococcus pneumonia, Klebsiella pneumonia, Haemophilus influenza, influenza virus, and pneumonia virus infections.

The researchers analyzed the data using machine learning after reviewing the pee test results. Based on just 20 sensors, they were able to develop algorithms that could distinguish between pneumonia and healthy controls, as well as determine if an infection was viral or bacterial.

The researchers also discovered that their sensors could discriminate between the five pathogens they examined, though with lesser accuracy than the test for viruses and bacteria. One avenue the researchers could follow is building algorithms that can not only discriminate between bacterial and viral infections but also identify the class of germs that are causing bacterial infection, allowing clinicians to select the appropriate medication to battle that type of bacteria.

The urine-based readout might potentially be detected using a paper strip in the future, similar to a pregnancy test, allowing for point-of-care diagnosis. In order to accomplish this, the researchers chose a subset of five sensors that could bring at-home testing closer to reality. More research is needed to see if the reduced panel would work in people, who have more genetic and clinical heterogeneity than mice.

Response patterns

The researchers also discovered certain trends in the host’s reaction to different forms of infection in their investigation. Proteases released by neutrophils were more prevalent in mice with bacterial infections, which was expected given that neutrophils respond more to bacterial infections than viral illnesses.

Viral infections, on the other hand, elicited protease activity in T cells and NK cells, which are known to be more responsive to viral infections. One of the sensors that produced the most signal was linked to granzyme B, a protease that causes programmed cell death. This sensor was discovered to be strongly activated in the lungs of mice with viral infections, and both NK and T cells were implicated in the response, according to the researchers.

The sensors were injected directly into the trachea in mice, but the researchers are currently working on human equivalents that may be administered using a nebulizer or an inhaler similar to an asthma inhaler. They’re also developing a method to detect the results using a breathalyzer rather than a urine test, which might provide results even faster.

The Bill and Melinda Gates Foundation, Janssen Research and Development, the National Cancer Institute’s Koch Institute Support (core) Grant, and the National Institute of Environmental Health Sciences all contributed to the study.

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Author: Muhammad Asim

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