Biological nanomaterials that exhibit repetitive functionalities with high spatial precision, density, and orientation are of great interest for the development and production of biosensors. In particular, biomaterials which can self-assemble on technologically relevant surfaces are of paramount importance. In this context, bacterial surface layer proteins (SLPs) are highly interesting nanomaterials as they fulfil all these requirements. Additionally, the proteinaceous lattice has water-filled pores and shows a thickness of only few nanometres. These features make self-assembled SPLs ideal as an intermediate surface for biosensors utilizing surface-sensitive techniques as read-out system. Moreover, the SLP lattice provides a surface where molecules can be bound in precise spatial distribution and orientation whereby almost no unspecific binding occurs.
To demonstrate the suitability of SLP lattices as smart surfaces, folate was chemically bound to the SLP from Lysinibacillus sphaericus CCM 2177 (SbpA). This construct was subsequently self-assembled on a gold-coated quartz disc. The specific recognition of folate receptors by the SbpA-immobilized folate was investigated by quartz crystal microbalance with dissipation monitoring (QCM-D). Folate receptors are highly expressed on the cell membrane of some cancer cells, such as the human breast adenocarcinoma cell line MCF-7. The developed sensor shows specific binding of MCF-7 cells whereas human liver cancer cells lacking folate receptors on their cell membrane give no shift in the QCM-D signal. This biosensor offers the ability to recognize cells in situ and in real time, and it is even possible to discriminate between different MCF-7 cell viability levels.
The proposed smart surface has several advantages like the nanometer thickness and low unspecific binding properties of the SLP lattice. These features increase the sensitivity and cell capturing efficiency. Hence, this biosensor comprising SbpA-folate biorecognition elements provides a promising strategy for designing smart sensing platforms to diagnose early-stage cancers.
