Date of Award


Document Type


Degree Name

Master of Science (MS)


Department of Chemistry

First Advisor

Jeremy D. Driskell


Influenza A H3N2, H1N1, and influenza B viruses primarily cause winter illness in humans, leading to significant morbidity and mortality in the population of the very young, the elderly, and people with chronic disease. In addition to the regular seasonal epidemics of influenza, influenza pandemics associated with the emergence of new influenza A strains are threatening due to high levels of mortality, social disruption, and economic losses. These novel strains are not affected by the human immunity developed to older strains of influenza, therefore can spread readily and infect a vast number of people. The most recent flu pandemic outbreak was in 2009, in which pandemic swine influenza A H1N1 was transmitted. Thus, an initiative to prevent human infections with new strains of influenza A virus with pandemic potential has been supported by the government and become a focus of many laboratories. The first step in any preventative measures is early detection. Therefore, it is essential to develop a detection platform that is capable of simultaneous multiplexing and exploitable for point-of-care (POC) analysis.

Virus culture, nucleic acid testing, and immunoassays are primary detection approaches to confirm acute human influenza virus infection. Nucleic acid testing has great sensitivity and specificity to subtype influenza strains, and high capacity for multiplexed detection. However, it is time and labor intensive, and expensive. Virus isolation is slow, costly, and not feasible for routine diagnostic testing. Immunoassays, in contrast, are known for availability, low-cost, accuracy, and versatility, and therefore have become a centerpiece in diagnostics. Among a number of analytical detection techniques developed for immunoassays, SERS (surface enhanced Raman spectroscopy) biosensing utilizing antibody-conjugated gold nanoparticles (Ab-AuNPs) is a promising virus detection technique providing high sensitivity (down to single molecule detection) and multiplexing (distinction of different strains of a single virus type).

Herein a simple, rapid, sensitive AuNP-based immunoassay was developed to quantitatively detect influenza A virus, utilizing dynamic light scattering (DLS) and surface enhanced Raman spectroscopy (SERS). The assay platform was established based on the principle of homogeneous format. Antigen-specific antibodies (Abs) were attached to the surface of gold nanoparticles (AuNPs), rendering the biospecificity for the detection. AuNPs serve as a signal generator or label. A biological sample containing targeted analytes was mixed with Ab-conjugated AuNPs (or AuNP probes); aggregation of nanoparticle was induced in the presence of the analyte(s). The antibody molecules on the particle surface recognized and bound to the analyte via the key-lock like mechanism, cross-linking AuNPs together to form aggregates. The quantification of antigen became the matter of detecting aggregation. The reaction happened in a timely fashion, oftentimes in a few minutes owing to the fast solution phase kinetics. No washing was required; therefore, time and labor were remarkably saved relative to heterogeneous assays. When utilizing this platform, alteration of different antigen-specific antibodies can perform detection of different antigen analytes individually (singleplexing). The combination of multiple types of AuNP probes in one assay allows simultaneously multiplexed detection.

In order to ensure the robustness of the assay, optimization for each stage of the platform design was thoroughly studied. The optimal conditions for maintaining the stability of the gold nanoparticles coated with monoclonal antibodies (mAbs) were investigated by varying pH, conjugation chemistry, mAbs concentrations, and blocking reagents. DLS is exploited to monitor the conjugation of the antibodies on AuNPs and verify the aggregate formation of the antigen-induced AuNP probes based on hydrodynamic diameter measurements. The DLS-based immunoassay has been demonstrated as an excellent rapid screening method to evaluate the specificity and affinity of antibody-antigen binding. Comparing to a conventional method for antibody screening (i.e. ELISA), a DLS assay requires only 30 min while it takes 24 h to perform an ELISA.

To address the urgent need for multiplexed detection, we have slightly modified the DLS assay to develop a SERS-based homogeneous immunoassay. Namely, Raman reporters and antibody were co-immobilized on the AuNPs to construct ERLs (extrinsic Raman labels). Raman reporters provide distinctive and amplified signal for detection. In order to detect multiple analytes, multiple types of ERLs were separately prepared; each type was a unique combination of one antigen-specific antibody and one Raman reporter. The ERLs were then mixed together and added to the sample. Aggregation was induced upon the introduction of the antigen to the suspension of ERLs on the order of minutes. ERLs of the same type were cross-linked via the antigen specific to the antibody conjugated to the very type of ERLs. The nonspecific ERLs remained unreacted if their antigens were not present in the sample. Once aggregation occurred, the SERS signals provided by the Raman reporters on the reacted ERLs were turned on. AuNPs in the aggregating state were in proximity to each other and created small gaps between them. Raman reporters once trapped in those gaps generated signal for detection. In theory, SERS analysis can be performed in solution but in reality poor plasmonic coupling between antibody-modified AuNP limits the SERS enhancement. However, dehydration of the aggregates reduces interparticle spacing to yield higher SERS signals. Therefore, separation of aggregated ERLs on a well-defined nanoporous membrane was applied to intensify the signal. The conditions for optimal filtration process have been investigated. Preliminary data have shown progress made toward a fully developed configuration for a portable multiplexed, sensitive, and rapid POC detection platform.


Imported from ProQuest Lai_ilstu_0092N_10612.pdf


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