Shedding Light on H. pylori Detection: A Fusion Protein Approach Unveiled through LIPS Method

The Luciferase Immunoprecipitation Systems (LIPS) method serves as a highly sensitive approach for quantitatively detecting antibodies to antigens, offering potential in identifying viral and bacterial infections. However, the substantial size of the luciferase-antigen fusion protein presents challenges in both production and folding. An alternative strategy employing epitopes rather than full length antigenic protein may circumvent issues associated with recombinant expression. Helicobacter pylori, a gram-negative bacterium, poses a risk of gastric cancer if untreated over time. This study focuses on the recombinant production of a fusion protein comprising in silico designed antigenic epitopes from the H. pylori urease protein and luciferase, aiming to reduce the fusion proteins size and thus augment its expression in the E. coli system. By employing bioinformatic analysis, sequences encoding the antigenic regions were pinpointed and subsequently amplified via PCR. A luciferase-linker-epitope construct was devised and constructed accordingly. The E. coli Bl21 (DE3) strain was utilized to express the recombinant chimeric protein, which was subsequently purified to achieve a state of homogeneity. The molecular weight of the fusion protein was estimated to be 75 kilodalton. Verification of the chimeric proteins proper folding and functionality was confirmed, as evidenced by a bioluminescence assay yielding an emission of 13.7 x 106 (RLU/s). Furthermore, western blot analysis authenticated the fusion proteins capability to bind specifically to H. pylori antibodies. These findings underscore the potential of the resultant protein as a promising candidate for H. pylori detection while also streamlining the recombinant production of LIPS fusion proteins. Key PointsO_LIEpitope-driven protein design boosts E. coli expression for LIPS advancement. C_LIO_LIImproved H. pylori detection aids early gastric cancer identification. C_LI