Dublin, Ireland – 2nd February 2021 – Aalto Bio Reagents is pleased to announce the availability of the first highly reactive recombinant Rubella Spike Ectodomain (E1-E2) antigen, code BM 6428, which has shown exceptional detection of both IgG and IgM antibodies in ELISA and bead-based immunoassays. Purified from recombinant expression in insect cells, this high-quality antigen has guaranteed lot to lot consistency and considerably shorter lead times for large lots compared to native antigen production. Using the protein sequence from the Rubella vaccine strain HPV-77, it was possible to produce a very reliable product, ready for use in the development of highly specific IgG and IgM assays.
Transmitted by droplets, Rubella continues to be a widespread infection, particularly in areas where vaccination rates are low. Although the disease typically presents as a mild rash in children, if contracted during pregnancy, the virus can lead to serious foetal abnormalities. Accurate detection of acute Rubella infection is therefore vital. However, reliable detection of IgM antibodies has proved challenging due to the non-specific interferences with other pathogens. It is believed this cross-reactivity is primarily linked to one of the three viral structural proteins – the capsid protein (C). By removing this protein and leaving the two major immunological targets – spike glycoproteins E1 and E2, this new antigen eliminates these potential IgM cross-reactivity issues, leading to less false positives.
CEO of Aalto Bio Reagents, Philip Noone, comments on how the new recombinant Rubella Spike Ectodomain (E1-E2) antigen is a strong contender for the replacement of native Rubella antigens in IVD assays – “There is a very high correlation for IgG and IgM antibody detection with our recombinant antigen versus a commercial native antigen, with our antigen showing 100% sensitivity and between 94.6% to 100% specificity in both ELISA and bead-based assays. Our capsid free antigen overcomes cross-reactivity difficulties and can clearly distinguish between positive and negative samples.”