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Host protease activity classifies pneumonia etiology.
- Source :
-
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2022 Jun 21; Vol. 119 (25), pp. e2121778119. Date of Electronic Publication: 2022 Jun 13. - Publication Year :
- 2022
-
Abstract
- Community-acquired pneumonia (CAP) has been brought to the forefront of global health priorities due to the COVID-19 pandemic. However, classification of viral versus bacterial pneumonia etiology remains a significant clinical challenge. To this end, we have engineered a panel of activity-based nanosensors that detect the dysregulated activity of pulmonary host proteases implicated in the response to pneumonia-causing pathogens and produce a urinary readout of disease. The nanosensor targets were selected based on a human protease transcriptomic signature for pneumonia etiology generated from 33 unique publicly available study cohorts. Five mouse models of bacterial or viral CAP were developed to assess the ability of the nanosensors to produce etiology-specific urinary signatures. Machine learning algorithms were used to train diagnostic classifiers that could distinguish infected mice from healthy controls and differentiate those with bacterial versus viral pneumonia with high accuracy. This proof-of-concept diagnostic approach demonstrates a way to distinguish pneumonia etiology based solely on the host proteolytic response to infection.
- Subjects :
- Animals
Biosensing Techniques
Disease Models, Animal
Humans
Machine Learning
Mice
Nanoparticles
COVID-19 genetics
Community-Acquired Infections classification
Community-Acquired Infections genetics
Community-Acquired Infections virology
Gene Expression Profiling
Peptide Hydrolases genetics
Pneumonia, Bacterial classification
Pneumonia, Bacterial genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1091-6490
- Volume :
- 119
- Issue :
- 25
- Database :
- MEDLINE
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Type :
- Academic Journal
- Accession number :
- 35696579
- Full Text :
- https://doi.org/10.1073/pnas.2121778119