Exosomal proteome analysis of human plasma to monitor sepsis progression

Highlights: • As low as 300 μL human plasma is sufficient for exosome isolation using our one-step density gradient ultracentrifugation. • Protein profiling of septic plasma exosomes are closely related to immune responses. • SPTLC3 may play important roles in development of sepsis. Exosomes are cell-derived vesicles containing RNA, lipid, and protein, which act in body immune response, intercellular signaling and some other important biological processes. Exosomes have been extensively studied in the past several years on their disease related mechanisms and potential roles to monitor disease progression as biomarkers. Compared with analyzing exosome RNA, comprehensive proteome profiling of exosomes in clinical samples (e.g. blood) are highly demanded but limited mainly due to lack of a reproducible method for efficient exosome extraction. In this study, we evaluated and optimized an exosome preparation approach using one-step ultracentrifugation through an Optiprep™ cushion. Exosomes prepared via this method and analyzed by mass spectrometry using Q-Exactive plus, has led to reproducible identification and quantification of 200 + proteins from human plasma samples of as little as 300 μL. Therefore, such a straightforward exosome extract method has enable us to deeply profile exosome proteomes from human blood at a scale of clinical studies. As a proof of principal, we practiced this approach in analyzing the exosome proteomic profiles of blood samples collected from a sepsis patient during six time points after diagnosis. Among the 238 proteins identified and quantified across the 6 samples, protein SPTLC3 involved in the sphingolipid metabolism, shows a negative correlation (p = 0.02, correlation coefficient = −0.984) with disease progression indicated by body temperature (BD) and C-reactive protein (CRP). Therefore, SPTLC3 could be an interesting target for future study on molecular mechanism of sepsis development, as well as potential classifier to monitor clinical progression of sepsis.