Khamis, O. M. | Search bioRxiv

bioRxiv2026

Interferon-γ promotes SMAP production by cytotoxic T lymphocytes in a thrombospondin 4 dependent manner

Cytotoxic T lymphocytes (CTLs) eliminate infected and cancerous cells by exocytosing cytotoxic granules, either as single-core granules (SCGs) releasing diffusible Granzyme B and Perforin, or as multi-core granules (MCGs) releasing these effectors as thrombospondin-1/4-encapsulated supramolecular attack particles (SMAPs). How CTLs differentially deploy these granule types remains unclear. We demonstrate that prolonged in vitro expansion and restimulation selectively enhance SMAP release, correlating with increased MCG maturation and thrombospondin-4 expression. Using high-resolution imaging, we identify fusion-competent MCG intermediates lacking SMAPs but releasing granzyme B diffusively. Mechanistically, interferon-{gamma} upregulates thrombospondin-4, driving MCG maturation and SMAP biogenesis, enhancing late-phase CTL killing efficiency against resistant targets. Consistent with this, THBS1 and THBS4 transcript levels appear elevated in melanoma-infiltrating CTLs compared with those during acute adenovirus infection. These findings define a stimulus-dependent, interferon-{gamma}-driven pathway tailoring CTL responses to chronic pathology and highlight opportunities for SMAP-targeted immunotherapies.

immunology↗

bioRxiv2024

Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis

Vesicle exocytosis is a fundamental component of intercellular communication, in all organisms. It has been studied for decades, using various imaging tools. Nevertheless, exocytosis research is still limited by the lack of reliable automated analysis procedures. To address this, we developed the Intelligent Vesicle Exocytosis Analysis Platform (IVEA), a nearly universal solution for analyzing exocytosis acquired with live cell imaging. IVEA is applicable to a wide variety of experimental model systems, microscopes and reporter fluorophores. IVEA combines state-of-the-art deep-learning and computer vision regimes to enable fully automated analysis of large data. IVEA runs as a FIJI plugin and does not require prior training or human intervention. IVEA is 60 times faster than manual analysis and is able to detect rare events often missed by the human eye. Overall, IVEA represents a breakthrough in the analysis of cellular secretory mechanisms and has a transformative potential for the exocytosis imaging field.

bioengineering↗