The major diagnostic VSG LiTat 1.3 of the human parasite Trypanosoma brucei gambiense is a trimer in solution
Human African trypanosomiasis (HAT) remains a significant health burden in sub-Saharan Africa, with serological diagnosis relying heavily on parasite variant surface glycoproteins (VSGs). In this study, we present evidence that LiTat 1.3 (a key VSG in the diagnosis of T. b. gambiense infections) displays a homotrimeric architecture in solution instead of the archetypal homodimeric structure expected for a VSG. This was demonstrated by adopting an integrative structural biology approach encompassing AlphaFold-based structure prediction, analytical gel filtration (AGF), size exclusion chromatography with multi-angle light scattering (SEC-MALS), and small-angle X-ray scattering (SAXS). Furthermore, the SAXS data demonstrate that the C-terminal domains of trimeric VSGs exhibit the same degree of flexibility as observed in dimeric VSGs. Hence, the biophysical characterization of LiTat 1.3 VSG adds to the limited, yet growing body of knowledge that certain VSG classes occur as homotrimers instead of homodimers. Authors SummaryHuman African trypanosomiasis (HAT) is caused by Trypanosoma brucei gambiense, a parasite transmitted by tsetse flies. To survive in the human host, these parasites cover themselves with a coat consisting of millions of identical copies of surface proteins called variant surface glycoproteins (VSGs). This VSG coat is regularly switched by the parasite to escape the immune system. Some of these VSGs, including one known as LiTat 1.3, are used in diagnostic tests to detect potentially infected patients. In our study, we discovered that, unlike most VSGs that form pairs of identical molecules (homodimers), LiTat 1.3 assembles into groups of three (homotrimers). Using structural and biophysical techniques, we showed that this trimeric form is stable in solution and retains the dynamic behavior observed in dimeric VSGs. Understanding how such structural variations arise and how they influence immune recognition may help explain why certain VSGs, like LiTat 1.3, are particularly effective in diagnosis and could ultimately guide the development of improved tools to monitor and control sleeping sickness.