Immunoinformatic analysis for identifying immunogenic antigens from the complete proteome of Giardia lamblia.

Abstract

Background: Giardia lamblia is a parasite that infects humans. To date, there is no vaccine available for human giardiasis. Thus, discovering new immunogenic antigens is crucial for the rational design of a vaccine.

Objectives: This study aimed to identify the main immunogenic antigens of G. lamblia from its entire proteome using immunoinformatic and data science techniques. To our knowledge, this is the first study to systematically identify immunogenic antigens of G. lamblia across its complete proteome, providing a comprehensive map of potential immunogenic antigens.

Methods: Briefly, FASTA sequences of G. lamblia isolates WB and GS were submitted to the NetMHCII 2.3 predictor. The analysis was conducted for five murine major histocompatibility complex (MHC)-II molecules: I-Ab, I-Ad, I-Ed, I-Ak, and I-Ek. Python 3.9 was used to develop custom code for data processing and analysis.

Findings: We identified 414 potential immunogenic polypeptides for isolate WB and 350 for isolate GS. For both isolates, most polypeptides contained peptides with high affinity for I-Ab and I-Ek. Notably, no polypeptides with high affinity for I-Ak were detected. Homologous potential immunogenic antigens (129 polypeptides) were identified in both isolates. The analysis revealed that 12 potential immunogenic polypeptides from isolate WB and 10 from isolate GS are part of the Giardia secretome. Additionally, promiscuous polypeptides that bind to at least two different MHC-II molecules were found in both isolates.

Main conclusions: These findings lay a valuable foundation for the rational development of a vaccine against human giardiasis and show a computational strategy that can be applied to the study of other pathogens.