Proteome profiling of whole plasma and plasma-derived extracellular vesicles facilitates the detection of tissue biomarkers in the non-obese diabetic mouse.
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Diaz Lozano IM, Sork H, Stone VM, Eldh M, Cao X, Pernemalm M, Gabrielsson S, Flodström-Tullberg M
Front Endocrinol (Lausanne) 13 (-) 971313 [2022-09-28; online 2022-09-28]
The mechanism by which pancreatic beta cells are destroyed in type 1 diabetes (T1D) remains to be fully understood. Recent observations indicate that the disease may arise because of different pathobiological mechanisms (endotypes). The discovery of one or several protein biomarkers measurable in readily available liquid biopsies (e.g. blood plasma) during the pre-diabetic period may enable personalized disease interventions. Recent studies have shown that extracellular vesicles (EVs) are a source of tissue proteins in liquid biopsies. Using plasma samples collected from pre-diabetic non-obese diabetic (NOD) mice (an experimental model of T1D) we addressed if combined analysis of whole plasma samples and plasma-derived EV fractions increases the number of unique proteins identified by mass spectrometry (MS) compared to the analysis of whole plasma samples alone. LC-MS/MS analysis of plasma samples depleted of abundant proteins and subjected to peptide fractionation identified more than 2300 proteins, while the analysis of EV-enriched plasma samples identified more than 600 proteins. Of the proteins detected in EV-enriched samples, more than a third were not identified in whole plasma samples and many were classified as either tissue-enriched or of tissue-specific origin. In conclusion, parallel profiling of EV-enriched plasma fractions and whole plasma samples increases the overall proteome depth and facilitates the discovery of tissue-enriched proteins in plasma. If applied to plasma samples collected longitudinally from the NOD mouse or from models with other pathobiological mechanisms, the integrated proteome profiling scheme described herein may be useful for the discovery of new and potentially endotype specific biomarkers in T1D.
Global Proteomics and Proteogenomics [Service]
PubMed 36246930
DOI 10.3389/fendo.2022.971313
Crossref 10.3389/fendo.2022.971313