Identification of Toxoplasma gondii adhesins through a machine learning approach

Toxoplasma gondii, as other apicomplexa, employs adhesins transmembrane proteins for binding and invasion to host cells. Search and characterization of adhesins is pivotal in understanding Apicomplexa invasion mechanisms and targeting new druggable candidates. This work developed a machine learning software called ApiPredictor UniQE V2.0, based on two approaches: support vector machines and multilayer perceptron, to predict adhesins proteins from amino acid sequences. By using ApiPredictor UniQE V2.0, five SAG-Related Sequences (SRSs) were identified within the Toxoplasma gondii proteome. One of those candidates, TgSRS12B, was cloned in plasmid pEXP5-CT/TOPO and expressed in E. coli BL21 DE3. The resulting recombinant protein was purified via affinity chromatography. Co-precipitation assays in CaCo and Muller cells showed interactions between TgSRS12B-His-tagged and the membrane fractions from both human cell lines. In conclusion, we demonstrated that ApiPre-dictor UniQE V2.0, a bioinformatic free software, was able to identify TgSRS12B as a new adhesin protein.

Automated summary

This study developed a machine learning software called ApiPredictor UniQE V2.0 to predict adhesins proteins in Toxoplasma gondii. Using this software, a new adhesin protein called TgSRS12B was identified and its interaction with the membrane fractions of human cells was confirmed.