Developing a Two-Dimensional Size-Exclusion Liquid Chromatography Platform for Isolating the High-Quality Extracellular Vesicles to Predict and Evaluate Metabolic Improvement Outcomes of Sleeve Gastrectomy

The direct analysis of plasma exosomal components still presents significant challenges due to the interference of high concentrations of albumin, immunoglobulins, and other abundant proteins. Herein, we developed a two-dimensional size-exclusion liquid chromatography (2D-SELC) platform to isolate high-purity exosomes from human plasma for downstream lipidomics analysis. Compared to the traditional method, our method avoids the error caused by manual operation and is easier to realize automation and standardization due to adopting a fully automatic sampling and fraction collection system. Remarkably, our method was successfully applied in the separation of preoperative plasma exosomes from 37 patients who were classified into three groups, with improvement in both blood glucose and triglycerides (GT), with improvement in blood glucose only (G), and with no improvement in blood glucose or triglycerides (NGT), and identified distinct preoperative plasma exosomal lipidomic biomarkers in the GT and G groups compared to NGT. The performance of these identified biomarkers for predicting improvements in blood glucose or triglycerides after sleeve gastrectomy was validated by three machine learning algorithms. Collectively, our work underscores the potential of preoperative plasma exosomal lipid biomarkers as powerful predictive tools for assessing metabolic improvements following SG, paving the way for enhanced patient stratification and personalized treatment strategies. We believe that the developed platform can be a versatile method for the separation of high-purity exosomes in different complex samples and even the separation of exosomes with different sizes, thus obtaining more bioinformation on exosomes while discovering potential biomarkers due to the substitutability of the chromatographic column.