Back

An anti-Galectin-3 intrabody improves primary and memory response of antigen-specific CD8+ T cells during viral infection

Singh, Y. J.; Sehrawat, S.

2026-09-18 immunology
10.64898/2026.09.16.751996 bioRxiv
Show abstract

Genetic ablation approaches are routinely used to establish gene function, but these are not beyond limitations. The intracellularly expressed camelid single-domain antibodies (sdAbs), or nanobodies, can specifically disrupt molecular interactions and, therefore, help ascertain their role in the process of cellular differentiation. The approach has not been evaluated in differentiating T cells or the stimulating DCs during viral infection. We modified the intracellular response of Galectin-3 (Gal-3) using an -Gal-3 intrabody (IB) in antigen-specific CD8+ T cells and assessed their differentiation patterns during a resolving Influenza A virus encoding SIINFEKL epitope (IAV: WSN-SIINFEKL). The -Gal-3 IB expressors, compared to the cells genetically depleted of Gal-3, exhibit a significantly prolonged activation, enhanced proliferation, and elevated cytokine production following in vitro stimulation. The -Gal-3 IB expressing cells show enhanced functionality and generate an efficient effector response, favoring the generation of memory precursor effector cells (MPECs: CD127hiKLRG1lo) over short-lived effector cells (SLECs: CD127loKLRG1hi) in IAV-infected animals. Such a differentiation pattern results in improved differentiation of effector memory (CD44hiCD62LloCCR7lo) cells amongst the -Gal-3 IB-expressing cells. The generated memory cells are efficiently recalled upon challenge infection with MHV68-SIINFEKL and help control the infection better. Therefore, modifying the intracellular response of Gal-3 using a sdAb could improve the primary and memory response of antigen-specific CD8+ T cells.

Matching journals

The top 6 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.