You are here

Proc Natl Acad Sci U S A DOI:10.1073/pnas.2121778119

Host protease activity classifies pneumonia etiology.

Publication TypeJournal Article
Year of Publication2022
AuthorsAnahtar, M, Chan, LW, Ko, H, Rao, A, Soleimany, AP, Khatri, P, Bhatia, SN
JournalProc Natl Acad Sci U S A
Volume119
Issue25
Pagese2121778119
Date Published2022 Jun 21
ISSN1091-6490
KeywordsAnimals, Biosensing Techniques, Community-Acquired Infections, COVID-19, Disease Models, Animal, Gene Expression Profiling, Humans, Machine Learning, Mice, Nanoparticles, Peptide Hydrolases, Pneumonia, Bacterial
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.

DOI10.1073/pnas.2121778119
Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/35696579?dopt=Abstract

Alternate JournalProc Natl Acad Sci U S A
PubMed ID35696579