Extraction, detection, and profiling of serum biomarkers using designed Fe3O4@SiO2@HA core–shell particles
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Serum biomarkers in the form of proteins (e.g. cluster of differentiation-44 (CD44)) have been demonstrated to have high clinical sensitivity and specificity for disease diagnosis and prognosis. Owing to the high sample complexity and low molecular abundance in serum, the detection and profiling of biomarkers rely on efficient extraction by materials and devices, mostly using immunoassays via antibody-antigen recognition. Antibody-free approaches are promising and need to be developed for real-case applications in serum to address the limitations of antibody-based techniques in terms of robustness, expense, and throughput. In this work, we demonstrated a novel approach using hyaluronic acid (HA)-modified materials/devices for the extraction, detection, and profiling of serum biomarkers via ligand-protein interactions. We constructed Fe3O4@SiO2@HA particles with different sizes through layer-by-layer assembly and for the first time applied HA-functionalized particles in the facile extraction and sequence identification of CD44 in serum by mass spectrometry. We also first validated HA-CD44 binding through electrochemical sensing using HA-modified electrodes in both standard solutions and diluted serum samples, achieving a detection limit of ~0.6 ng/mL and a linear response range from 1 ng/mL to 10 μg/mL. Furthermore, we performed profiling of HA-binding serum proteome, providing a new preliminary benchmark for the construction of future databases, and we investigated selected surface chemistries of particles for the capture of proteins in serum. Our work not only resulted in the development of a platform technology for CD44 extraction/detection and HA-binding proteome identification, but also guided the design of ligand affinity-based approaches for antibody-free analysis of serum biomarkers towards diagnostic applications.
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Extraction, detection, and profiling of serum biomarkers using designed Fe3O4@SiO2@HA core–shell particles
Abstract
Serum biomarkers in the form of proteins (e.g. cluster of differentiation-44 (CD44)) have been demonstrated to have high clinical sensitivity and specificity for disease diagnosis and prognosis. Owing to the high sample complexity and low molecular abundance in serum, the detection and profiling of biomarkers rely on efficient extraction by materials and devices, mostly using immunoassays via antibody-antigen recognition. Antibody-free approaches are promising and need to be developed for real-case applications in serum to address the limitations of antibody-based techniques in terms of robustness, expense, and throughput. In this work, we demonstrated a novel approach using hyaluronic acid (HA)-modified materials/devices for the extraction, detection, and profiling of serum biomarkers via ligand-protein interactions. We constructed Fe3O4@SiO2@HA particles with different sizes through layer-by-layer assembly and for the first time applied HA-functionalized particles in the facile extraction and sequence identification of CD44 in serum by mass spectrometry. We also first validated HA-CD44 binding through electrochemical sensing using HA-modified electrodes in both standard solutions and diluted serum samples, achieving a detection limit of ~0.6 ng/mL and a linear response range from 1 ng/mL to 10 μg/mL. Furthermore, we performed profiling of HA-binding serum proteome, providing a new preliminary benchmark for the construction of future databases, and we investigated selected surface chemistries of particles for the capture of proteins in serum. Our work not only resulted in the development of a platform technology for CD44 extraction/detection and HA-binding proteome identification, but also guided the design of ligand affinity-based approaches for antibody-free analysis of serum biomarkers towards diagnostic applications.
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Acknowledgements
We gratefully thank the financial support from National Natural Science Foundation of China (NSFC)(Nos. 81550110257 and 81401542), Shanghai Science and Technology Commission(No. 16441909300). This work is also sponsored by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (No. TP2015015).
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