| Carbohydrates (glycans) as a kind of important informational molecules in organisms, often play key roles in a lot of physiological and pathological processes including cell adhesion, signal transduction, tumor immunology, inflammation, and so on. Some glycosylated proteins (glycoproteins) can be used as biomarkers in clinical diagnosis for many diseases, the expression of glycans (such as mannose and sialic acid) on the cell surface is closely associated with tumor progression and metastasis, and glycans on influenza A virus are well known to be in involved in the virus infection to the host cells. Therefore, sensitive quantification of glycan related molecules in complex biological samples is of great significance.The newly developed elemental labeling based inductively coupled plasma mass spectrometry (ICP-MS) method provides a powerful approach for quantitative analysis of biomolecules. With various available elemental tags, ICP-MS based approach is prosperous for biomolecules quantification in recent years with the merits of simple quantification concepts, high sensitivity, low matrix effects, wide dynamic range, and outstanding ability for multiple targets analysis. The feasibility for the detection of various biomolecules like proteins, DNA and RNA, and even bacteria and cancer cells by ICP-MS with element-tags has been demonstrated over the past decade. However, the applications of this approach in glycan related molecules analysis are rare. Hence, it’s necessary to develop new elemental labeling based ICP-MS methods for glycan related molecules analysis and expand its application potential in life-science related research. As two kinds of classic recognition molecules for carbohydrates, lectins and boronic acid are quite promising to facilitate the elemental labeling of target glycan related molecules.In addition, highly efficient amplification strategies are needed to further improve the sensitivity of ICP-MS based bioassays for low abundant targets detection in bioanalysis. As an ideal elemental tag in ICP-MS based bioassays, gold nanoparticles (AuNPs) have advantages of good biocompatibility, facility of preparation, and signal amplification effect due to the hundreds or thousands of Au atoms existing in a single NP. Besides, hybridization chain reaction (HCR) is a kind of DNA amplification strategy with merits of high efficiency, simplicity, and no need for enzyme catalysis or thermal cycles, which can be applied to improve the sensitivity of elemental labeling based ICP-MS strategy.The overall objectives of this dissertation are to develop new elemental labeling strategy based on glycan recognition, explore new signal amplification approach for ICP-MS based bioanalytical method, and demonstrate their applications in bioanalysis. The major contents of this dissertation are described as follows:(1) A new approach of magnetic immunoassay-ICP-MS was established for simultaneous quantitative analysis of glycoproteins.4-mercaptophenylboronic acid functionalized magnetic beads were prepared to selectively capture glycoproteins, while antibody conjugated AuNPs and silver nanoparticles (AgNPs) were synthesized as element tags to label two different glycoproteins for ICP-MS detection. Two biomarkers alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA) were taken as model glycoproteins in the magnetic immunoassay, and the obtained limits of detection (LODs) for AFP and CEA were 0.086 μg L-1 and 0.054 μg L-1 with the relative standard deviations (RSDs, n=7, c=5 μg L-1) of 6.5% and 6.2% for AFP and CEA, respectively. Linear range for both AFP and CEA was 0.2-50 (μg L-1. To validate the applicability of the proposed method, human serum samples were analyzed, and the obtained results were in good agreement with that obtained by the clinical chemiluminescence immunoassay.(2) A simple, sensitive assay protocol for the analysis of sialic acids on the cancer cell surface was established by elemental labeling based ICP-MS detection. The method was based on the selective recognition of sialic acids by biotinylated phenylboronic acid (biotin-APBA) at physiological pH and signal enhancement of AuNPs in ICP-MS when AuNPs were used as elemental tags labeled on biotin-APBA. The proposed method exhibited good specificity towards cancer cells over normal cells. Taking HepG2 and MCF-7 cells as two model cancer cells, competitive experiments were performed to estimate the expression level of sialic acids on the cancer cell surface, and it was found that the average numbers of sialic acids expressed on the single HepG2 and MCF-7 cell surface were 5.4x109 and 7.0x109, respectively. With sialic acid as the biomarker for cancer cells, the method was further used for cell detection. The LODs in terms of cell number for HepG2 and MCF-7 cells were 120 and 64, respectively. The linear ranges for HepG2 cells and MCF-7 cells were 300-10000 and 170-11000, respectively. And the RSDs for nine replicate determinations of ca.1000 HepG2 and MCF-7 cells were 9.6% and 8.9%, respectively.(3) An efficient, specific, and sensitive approach for detection of tumor cells was developed by using ICP-MS with AuNPs labeling and hybridization chain reaction (HCR) amplification. In the established method, antibodies against epithelial cell adhesion molecule (anti-EpCAM) conjugated magnetic beads (MBs) were used for selective capture of tumor cells from peripheral blood through magnetic isolation under an external magnetic field. Biotin modified DNA concatamer was prepared by HCR and further specifically bound to streptavidin-AuNPs conjugates to prepare the AuNPs labeled DNA concatamer (AuNPs-DNA concatemer) as the signal probe for tumor cell labeling and ICP-MS detection. Taking HepG2 cells as the model cell, the LODs of this ICP-MS based method for HepG2 cells was as low as 15 cells, and the linear range was 40-8000 cells with the RSD for seven replicate detections of 200 HepG2 cells was 8.7%. Furthermore, the applicability of the method for the analysis of peripheral blood samples was demonstrated by the spiking tests.(4) A new elemental labeling based ICP-MS method for sensitive detection of H9N2 virus particles was developed by using lectin recognition and dual signal amplification strategy. The approach was based on the lectin affinity to glycoproteins on influenza A virus and signal enhancement of ICP-MS detection by using AuNPs labeling and HCR amplification. Antibodies against H9N2 hemagglutinin (anti-H9N2 HA) conjugated MBs were used for selective capture of H9N2 virus from complex sample matrix. By taking Con A as the bridge, AuNPs labeling and HCR based dual amplification strategy was successfully introduced into virus particle detection. The LODs of this ICP-MS based method for H9N2 virus was 0.12 μg L-1, and the linear range was 0.4-50 μg L-1 with the RSD for seven replicate detections of 2 μg L-1 H9N2 virus was 7.9%. The application potential of the method for real sample analysis was demonstrated by the spiking tests in chicken dung samples. |
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