Molecularly Imprinted Plasmonic Substrates for Specific and Ultrasensitive Immunoassay of Trace Glycoproteins in Biological Samples.

Assays of glycoproteins hold significant biological importance and clinical values, for which immunoassay has been the workhorse tool. As immunoassays are associated with disadvantages such as poor availability of high-specificity antibodies, limited stability of biological reagents, and tedious procedure, innovative alternatives that can overcome these drawbacks are highly desirable. Plasmonic immunosandwich assay (PISA) has emerged as an appealing alternative to immunoassay for fast and sensitive determination of trace glycoproteins in biosamples. Plasmonic substrates play key roles in PISA, not only in determining the specificity but also in greatly influencing the detection sensitivity. Herein, we report a new type of molecularly imprinted plasmonic substrates for rapid and ultrasensitive PISA assay of trace glycoproteins in complex real samples. The substrates were fabricated from glass slides, first coated with self-assembled monolayer (SAM) of gold nanoparticles (AuNPs) and then molecularly imprinted with organo-siloxane polymer in the presence of template glycoproteins. The prepared molecularly imprinted substrates exhibited not only a significant plasmonic effect but also excellent binding properties, ensuring the sensitivity as well as the specificity of the assay. Alkaline phosphatase (ALP) and α-fetoprotein (AFP), glycoproteins that are routinely used as disease markers in clinical diagnosis, were used as representative targets. The limit of detection (LOD) was 3.1 × 10-12 M for ALP and 1.5 × 10-14 M for AFP, which is the best among the PISA approaches reported. The sample volume required was only 5 μL, and the total time required was within 30 min for each assay. Specific and ultrasensitive determination of ALP and AFP in human serum was demonstrated. Because many disease biomarkers are glycoproteins, the developed PISA approach holds great promise in disease diagnostics.