Exosomes are cell-derived, phospholipid bilayer-enclosed vesicles that play important roles in intercellular interactions and regulate many biological processes. Accumulating evidence suggests that serum exosomes are potential biomarkers for the early diagnosis of cancer. To aid the downstream molecular analyses of tumour-secreted exosomes, purified exosomes are highly desirable. However, current techniques for exosome isolation are time-consuming and highly instrument-dependent, with limited specificity and recovery. Thus, rapid and efficient methods are strongly needed for both basic research and clinical applications. Here, we present a novel strategy for facile exosome isolation from human serum by taking advantage of the specific interaction of TiO₂ with the phosphate groups on the lipid bilayer of exosomes. Due to their simplicity and highly affinitive binding, model exosomes can be reversibly isolated with a high recovery (93.4%). Downstream characterization and proteome profiling reveal that high-quality exosomes can be obtained from human serum by this TiO₂-based isolation method in 5 min, which is a fraction of the time required for the commonly used ultracentrifugation method. We identified 59 significantly up-regulated proteins by comparing the serum exosomes of pancreatic cancer patients and healthy donors. In addition to the 30 proteins that were reported to be closely related to pancreatic cancer, we found an additional 29 proteins that had not previously been shown to be related to pancreatic cancer, indicating the potential of this novel method as a powerful tool for exosome isolation for health monitoring and disease diagnosis.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-CoV-2) is still raging all over the world. Hence, the rapid and sensitive screening of the suspected population is in high demand. The nucleocapsid protein (NP) of SARS-CoV-2 has been selected as an ideal marker for viral antigen detection. This study describes a lateral flow immunoassay (LFIA) based on colloidal gold nanoparticles for rapid NP antigen detection, in which sensitivity was improved through copper deposition-induced signal amplification. The detection sensitivity of the developed LFIA for NP antigen detection (using certified reference materials) under the optimized parameters was 0.01 μg/mL and was promoted by three orders of magnitude to 10 pg/mL after copper deposition signal amplification. The LFIA coupled with the copper enhancement technique has many merits such as low cost, high efficiency, and high sensitivity. It provides an effective approach to the rapid screening, diagnosis, and monitoring of the suspected population in the COVID-19 outbreak.

Glycoproteins are involved in a variety of biological processes. More than one-third of the plasma protein biomarkers of tumors approved by the FDA are glycoproteins, and could improve the diagnostic specificity and/or sensitivity. Therefore, it is of great significance to perform the systematic characterization of plasma N-glycoproteome. In previous studies, we developed an integrated method based on the combinatorial peptide ligand library (CPLL) and stepped collision energy/higher energy collisional dissociation (sceHCD) for comprehensive plasma N-glycoproteome profiling. Recently, we presented a new fragmentation method, EThcD-sceHCD, which outperformed sceHCD in the accuracy of identification. Herein, we integrated the combinatorial peptide ligand library (CPLL) into EThcD-sceHCD and compared the performance of different mass spectrometry dissociation methods (EThcD-sceHCD, EThcD, and sceHCD) in the intact N-glycopeptide analysis of prostate cancer plasma. The results illustrated that EThcD-sceHCD was better than EThcD and sceHCD in the number of identified intact N-glycopeptides (two-folds). A combination of sceHCD and EThcD-sceHCD methods can cover almost all glycoproteins (96.4%) and intact N-glycopeptides (93.6%), indicating good complementarity between the two. Our study has great potential for medium- and low-abundance plasma glycoprotein biomarker discovery.