A Molecular Diagnostic Platform Devised from Supramolecular Gold-Oligo NanoNet Assembly for Differentiating RhD...

Blood transfusion is integral to patients with blood-related disorders, necessitating point-of-care diagnosis for further treatment. Successfully differentiating Rh antigens based on their genotypes is fundamental for mitigating post-transfusion complexities. Inspired by the need for extended blood typing, we demonstrate the use of a supramolecular oligonucleotide-conjugated gold nanoassembly (Au-Oligo-net) to determine the RhD-positive and RhD-negative samples. In the presence of the RhD-positive phenotype, the Au-Oligo-net assemblies targeted toward RHD exons 5, 7, and 10 will undergo complementary binding with their respective exon sequence, where the addition of duplex-specific nuclease causes specific cleavage at the hybridized genetic segments. This results in the deagglomeration of the nanonet assembly, causing a significant shift in their plasmonic spectra. On the other hand, in the absence of the target exon, the Au-Oligo-net remains aggregated, providing a distinct difference between the two RhD phenotypes. The sensing principle has been validated using varied bioanalytical techniques, including UV-visible spectroscopy, transmission electron microscopy, small-angle neutron scattering, photoacoustic response, etc. The functional applicability of the designed platform has been substantiated using human blood specimens, which were collected from different transfusion-dependent patients of varying RhD phenotypes, who were unlikely to have any weak or partial D signature. Experimental results indicate that the sensing platform can distinguish RhD-positive samples from a limited set of RhD-negative samples, primarily those with RHD deletion, with a limit of detection (LOD) of ∼12.5 pg/μL for RhD-positive DNA. Given the current workflow requirements, this plasmonic sensing strategy should be considered as a bench-top proof-of-concept platform with future potential for simplification and potential applicability in resource-limited settings and in developing countries.