Vrachnos, D. | bioRxiv Science

bioRxiv2025

CD2 expression is co-regulated with stemness- and exhaustion-associated factors in human T cells

The CD2-CD58 pathway has been highlighted as a major player in anti-tumour T cell immunity. Our study reveals that CD2 costimulation strength significantly correlates with T cell activation, the average number of cell divisions, fold expansion, and IFN-{gamma} production. Our findings suggest that the correlation of CD2 strength with the level of CD25 expression is a potential regulatory mechanism by which CD2 strength enhances above proliferation parameters. We find that human brain cancer tumour-infiltrating CD8+ and CD4+ T cells exhibit reduced levels of CD2, suggestive of a compromised CD2 strength upon CD2 engagement. Through a genome-wide CRISPR-Cas9 knockout screen, we identified two epigenetic regulators, SUZ12 and BAP1, as positive modulators of CD2 expression. We demonstrate that BAP1 is crucial for the upregulation and sustained high expression of CD2 following T cell activation. We reveal that CD2 is co-regulated with other co-stimulatory/inhibitory receptors, and factors associated with T cell stemness and exhaustion, in a dose-dependent manner. Importantly, we rescue the loss of CD2 due to BAP1 knockout by pharmacological inhibition of histone deacetylases making this a harnessable regulatory pathway. The insight from our study enhance our understanding of CD2-mediated T cell regulation and identify essential regulators of this pathway.

immunology↗

bioRxiv2024

Accurate Predictions of Phase Separating Proteins at Single Amino Acid Resolution

Liquid-liquid phase separation (LLPS) is a molecular mechanism that leads to the formation of membraneless organelles inside the cell. Despite recent advances in the experimental probing and computational prediction of proteins involved in this process, the identification of the protein regions driving LLPS and the prediction of the effect of mutations on LLPS are lagging behind. Here, we introduce catGRANULE 2.0 ROBOT (R - Ribonucleoprotein, O - Organization, in B - Biocondensates, O - Organelle, T - Types), an advanced algorithm for predicting protein LLPS at single amino acid resolution. Integrating physico-chemical properties of the proteins and structural features derived from AlphaFold models, catGRANULE 2.0 ROBOT significantly surpasses traditional sequence-based and state-of-the-art structure-based methods in performance, achieving an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.76 or higher. We present a comprehensive evaluation of the algorithm across multiple organisms and cellular components, demonstrating its effectiveness in predicting LLPS propensities at the single amino acid level and the impacts of mutations on LLPS. Our results are robustly supported by experimental validations, including immunofluorescence microscopy images from the Human Protein Atlas. catGRANULE 2.0 ROBOTs potential in protein design and mutation control can improve our understanding of proteins propensity to form subcellular compartments and help develop strategies to influence biological processes through LLPS. catGRANULE 2.0 ROBOT is freely available at https://tools.tartaglialab. com/catgranule2.

biochemistry↗