Extracellular vesicles (EVs) are cell-derived membranous vesicles in nearly all biologicalfluids, including blood and urine. EVs carry a great number of cargos such as proteins, nucleic acids, and lipids. EVs from the parent cells could transfer their cargos to the recipient cells, serving as an important route for cell-cell communication. In particular, small EVs generated from the endolysosomal pathway (∼50-200 nm) have attracted interest as a suitable biomarker for cancer diagnostics and treatment monitoring, because they carry valuable biological information, and have molecular components reflecting the physiological status of their cells of origin. However, due to their small size, high heterogeneity, and low abundance, analysis of cancer cell-derived EVs is challenging, and the current EV analysis techniques are suffered from the limited detection range and/or the requirement of labor-intensive extraction steps. This thesis focuses on developing different methods which are rapid, simple, and sensitive to overcome some of these challenges. This research describes the development of three types of enzyme-mimicking nanomaterials to enable rapid and sensitive EV detection. Chapter II is about the design and employment of the CuS-enclosed microgels that exhibited the capability to catalyze the decomposition of peroxide for chemiluminescence production. The microgels can be applied for rapid EV isolation and sensitive quantification. The work described in Chapter III centered on the bimetallic metal organic framework (MOF) of Fe/Co-MIL-88(NH2) that showed high peroxidase-like activity and can workVI together with glucose oxidase (GOx) in the cascade enzymatic reactions to oxidize the peroxidase substrate with the input of glucose. An assay that applied the cascade reaction catalyzed by both the peroxidase-mimicking Fe/Co-MIL-88(NH2) and the GOx for sensitive and visible EV detection was thus developed. In Chapter IV, the bimetallic MOF was further improved by substituting the ligand used in MOF construction to enhance material stability and accommodate chemiluminescence as the signaling method. The limit of detection for EV analysis was much reduced, with the dynamic range much expanded, compared to the previous design. All three methods reported in this dissertation offer great low limits of detection between 10 ~ 104 EV particles/mL. These limits are all lower those of ELISA and NTA (106 ~ 108 particles/mL), which are the gold standards for EV detection. The reported methods are also rapid, with the enzymemimicking nanomaterials assisting with EV extraction to eliminate the needs for extra sample processing prior to detection. The enzyme-mimicking sensing materials developed in my dissertation work are inexpensive to fabricate and simple to use, suitable for serving as the signal amplification tools in a point-of-care diagnostic device deployable in the field and operated by minimally-trained personnel.

Extracellular vesicles (EVs) are cell-derived membranous vesicles that exist in nearly all biological fluids, including blood and urine; and carry a great number of cargo molecules such as protein, nucleic acids, and lipid. They may play important roles in cell-cell communication and modulation of pathological processes, which, however, are not yet well understood, calling for highly sensitive, specific, and rapid methods for EV detection and quantification in biological samples. Here, we report the CuS-enclosed microgels that not only help enrich EVs carrying specific protein markers from complex biomatrices, but also produce strong chemiluminescence (CL) to realize sensitive detection of the target EVs. A detection limit of 10⁴ EV particles/mL was achieved with these microgels by targeting EV proteins like CD63 and HER2, with a dynamic range up to 10⁸ particles/mL. Direct detection of EVs in human serum and cell culture medium without tedious sample preparation was demonstrated, consuming much less sample compared to ELISA and Western Blot. We envision that our method will be valuable for quick quantification of EVs in biological samples, benefiting disease monitoring and functional study.