Back

Antibodies to protozoan variable surface antigens induce antigenic variation

Tenaglia, A. H.; Lujan, L. A.; Rios, D. N.; Midlej, V.; Iribarren, P. A.; Molina, C. R.; Berazategui, M. A.; Torri, A.; Saura, A.; Peralta, D. O.; Rodriguez-Walker, M.; Fernandez, E. A.; Petiti, J. P.; Serradell, M. C.; Gargantini, P. R.; Alvarez, V. E.; de Souza, W.; Lujan, H. D.

2022-06-22 microbiology
10.1101/2022.06.21.497077 bioRxiv
Show abstract

The genomes of most protozoa encode families of variant surface antigens, whose mutually exclusive changes in expression allow parasitic microorganisms to evade the host immune response1,2. It is widely assumed that antigenic variation in protozoan parasites is accomplished by the spontaneous appearance within the population of cells expressing antigenic variants that escape antibody-mediated cytotoxicity1,2. Here we show, both in vitro and in animal infections, that antibodies to Variant-specific Surface Proteins (VSPs) of the intestinal parasite Giardia lamblia are not cytotoxic, inducing instead VSP clustering into liquid-ordered phase membrane microdomains that trigger a massive release of microvesicles carrying the original VSP and switch in expression to different VSPs by a calcium-dependent mechanism. Surface microvesiculization and antigenic switching are also stimulated when Trypanosoma brucei and Tetrahymena thermophila are confronted to antibodies directed to their GPI-anchored variable surface glycoproteins. This novel mechanism of surface antigen clearance throughout its release into microvesicles coupled to the stochastic induction of new phenotypic variants not only changes the current paradigm of spontaneous antigenic switching but also provides a new framework for understanding the course of protozoan infections as a host/parasite adaptive process.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.