Work

Microbiota in septic lungs using extracellular vesicle proteomics in bronchoalveolar lavage fluid 3180

Year: 2025

Type: article

Abstract: Description Heterogeneous pulmonary sepsis has an unacceptably high mortality rate of up to 48% in severe patients, characterized by inflammation, lung tissue injury, and hypoxia. Identification of pathogenic microbes is essential for practicing personalized medicine with specific and effective therapies. To mitigate the effects of long-term storage on protein stability, we extracted extracellular vesicles and generated a proteomics dataset by performing LC-MS/MS to analyze EV peptides. The proteomics data was analyzed using R. Different taxonomy, functional annotation, Shannon index, and correlations to clinical variables were observed between various stages of the diseases. AUC identified potential microbial proteins as diagnostic biomarkers. Our study suggests that extracellular vesicle (EV) proteomics is an effective strategy for analyzing long-term stored liquid biopsies. Microbial EV proteins can serve as biomarkers and can be utilized for the identification of druggable targets. Funding Sources Supported by NIH/HL134828. Topic Categories Translational and Interventional Immunology (TI)

Source: The Journal of Immunology

DOI: 10.1093/jimmun/vkaf283.1009

Authors: Honglong James Ji, Runzhen Zhao, Nan Miles Xi, Mark Qiao, Shichao Feng, Xuan Guo

Institution: Loyola University Chicago

Language: English

Topic: Extracellular vesicles in disease

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: National Institutes of Health