In-silico classification and antigen library expression of Plasmodium falciparum STEVOR hypervariable infected erythrocyte surface-expressed multivariant protein family

Abstract

Abstract Background Malaria pathogenesis is dependent on complex interactions between host and parasite factors, where variant surface antigens such as the Pf EMP1 protein family play a critical role in disease severity through various mechanisms, including immune evasion, cytoadherence and sequestration. The under characterised infected erythrocytes variant surface-expressed antigens of the STEVOR protein family are also implicated in cytoadherence and rosette formation exhibiting high antigenic variability, potentially contributing to parasite immune evasion. This study describes a novel approach for the construction of a comprehensive library of STEVOR recombinant antigens. Methods This study used all available STEVOR protein sequence data from the PlasmoDB database to classify the variability between STEVOR members within isolates and between isolates. We have used bioinformatic and mathematical approaches to design an in-silico model to study the protein family variability with 100% reproducibility when performed on the same data set. Using information from the model, we have designed constructs and have expressed them with the CyDisCo co-expression plasmid to create the first STEVOR recombinant antigen library in a competent E. coli expression system. Finally, we have proven the recombinants antigenicity using the multiplex magnetic bead-based assay: Luminex. Results The large hypervariable domain of STEVOR protein family exhibited the highest variability with a mean diversity of 52.1%, as compared to the semi-conserved and the conserved STEVOR domains. The variability was captured in a library of 13 representative sequences, mostly derived from West African isolates. Those variants were expressed as recombinant proteins in BL21(DE3) E. coli competent cells together with the CyDisCo co-expression plasmid. The recombinants varied in expression levels, but not in antigenicity. Three semi-conserved recombinant antigens were also expressed as controls and those although with smaller size, demonstrated higher reactivity as compared to the variable domain recombinants. Conclusions This study presents an in-silico model that effectively elucidates the spatial relationship between amino acid sequences, applicable to sequence data from any organism. Moreover, it presents the first library of STEVOR hypervariable domain recombinant antigens. Expressed antigens have potential applications in serological studies as indicators of exposure to infection and to further dissect STEVOR variants associated with severe malarial disease outcome.