Preparation of anti-influenza virus nanobodies and their applications in nanobody-ELISA

To develop nanobodies with broad-spectrum reactivity, specificity, and high sensitivity that can be used for detecting multiple subtypes of influenza A virus, and to establish a nanobody-based enzyme-linked immunosorbent assay (ELISA) method.

Gene sequences of twelve nanobodies against influenza A virus were retrieved from the National Center for Biotechnology Information (NCBI) and nanobody databases. The nanoantibodies were prepared using molecular biological techniques including gene synthesis and recombinant expression. The binding activity, specificity, sensitivity, and affinity of these nanobodies were determined by ELISA screening and Gator affinity analysis. A double-antibody sandwich ELISA assay was established by combining the selected nanobody with a traditional mouse monoclonal antibody.

Twelve nanobodies were expressed and purified. Two nanobodies capable of binding to multiple subtypes of influenza virus including H1, H3, H5, H7, and H9 were obtained and designated as VHH54 and KV108. Both nanobodies showed no cross-reactivity with other respiratory virus antigens. Furthermore, the KV108 nanobody exhibited the highest binding affinity, with a dissociation constant of 5.94×10^-9 mol/L for the influenza virus nucleoprotein (NP), and the lowest detection concentration for the NP antigen reached 0.00064 μg/mL. The double-antibody sandwich ELISA, using a combination of KV108 and a mouse monoclonal antibody, could sensitively detect the five common subtypes of influenza A virus (H1N1, H3N2, H5N1, H7N9, and H9N2). The lowest detection limit reached 110-403 PFU/mL, which was higher than that of the commercial colloidal gold kitfor influenza virus detection.

This study has identified a nanobody KV108, which is capable of binding to multiple subtypes of influenza virus, and established a nanobody-based ELISA method that can detect multiple subtypes of influenza A virus. This study can facilitate the development of nanobody-based influenza detection technologies.