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Accurate antigen detection is imperative for clinicians to diagnose disease, assess treatment success, and predict patient prognosis. The most common technique used for the detection of disease-associated biomarkers is the enzyme linked immunosorbent assay ELISA. In an ELISA, primary antibodies are incubated with biological samples containing the biomarker of interest. Then, detectible secondary antibodies conjugated with horseradish peroxidase HRP bind the primary antibodies. Upon addition of a color-changing substrate, the samples provide a colorimetric signal that directly correlates to the targeted biomarker concentration. While ELISAs are effective for analyzing samples with high biomarker content, they lack the sensitivity required to analyze samples with low antigen levels. We hypothesized that the sensitivity of ELISAs could be enhanced by replacing freely delivered primary antibodies with antibody-nanoparticle conjugates that provide excess binding sites for detectible secondary antibodies, ultimately leading to increased signal. Here, we investigated the use of nanoshells NS decorated with antibodies specific to epidermal growth factor receptor EGFR as a model system EGFR-NS. We incubated one healthy and two breast cancer cell lines, each expressing different levels of EGFR, with EGFR-NS, untargeted NS, or unconjugated EGFR antibodies, as well as detectable secondary antibodies. We found that EGFR-NS consistently increased signal intensity relative to unconjugated EGFR antibodies, with a substantial 13-fold enhancement from cells expressing high levels of EGFR. Additionally, 40x more unconjugated antibodies were required to detect EGFR compared to those conjugated to NS. Our results demonstrate that antibody-nanoparticle conjugates lower the detection limit of traditional ELISAs and support further investigation of this strategy with other antibodies and nanoparticles. Owing to their enhanced sensitivity, we anticipate that nanoparticle-modified ELISAs can be used to detect low levels of biomarkers found in various diseases, such as cancers, tuberculosis, and rheumatoid arthritis, and may ultimately enable earlier diagnosis, better prognostication, and improved treatment monitoring.



Author: Margaret M. Billingsley, Rachel S. Riley, Emily S. Day

Source: http://plos.srce.hr/



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