ArticleScientific reports2026
Modified protein selection strategy based on Escherichia coli's Hitchhiker transport and validation through selection of nanobodies targeting bovine interferon gamma.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The Escherichia coli hitchhiker co-translocation mechanism has been adapted as a screening platform known as Functional Ligand-binding Identification by Tat-based Recognition of Associating Proteins (FLI-TRAP) for identifying and isolating interacting proteins. Traditional FLI-TRAP systems utilize either monocistronic or bicistronic expression constructs. However, in the context of selecting single-domain antibody fragments, or ‘nanobodies’ (Nbs), specific to bovine interferon-gamma (bIFN-γ), the monocistronic system produces insufficient expression levels while the original bicistronic system is prone to false positives due to potential structural rearrangements that allow antibiotic resistance independent of Nb–antigen binding. To overcome these limitations, we have modified an improved bicistronic FLI-TRAP system that reduces the rate of false positives and enhances the fidelity of the selection process. This optimized system was validated through isolating anti-bIFN-γ Nbs from a fully synthetic yeast display library. Candidate Nbs were first enriched using magnetic-activated cell sorting (MACS), followed by screening via the improved FLI-TRAP assay. The two best clones, B7 and N5, displayed specific binding to bIFN-γ, with dissociation constants (KD) of 81.6 nM and 575 nM, respectively. Further characterization revealed that B7 exhibited high specificity, low polyreactivity, and effective detection of bIFN-γ in bovine plasma samples, compared with the BOVIGAM kit, a commercially approved and widely used diagnostic tool for bovine tuberculosis. This study demonstrates the utility of the improved bicistronic FLI-TRAP system as a reliable, scalable, and cost-effective platform for selecting high-affinity Nbs. The system offers a promising alternative for developing Nb-based diagnostic kits, which are particularly suited for use in resource-limited settings.
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