Rapid cloning of antigen-specific T-cell receptors by leveraging the cis activation of T cells

Multimodal probing of T-cell recognition with hexapod heterostructures

Studies using antigen-presenting systems at the single-cell and ensemble levels can provide complementary insights into T-cell signaling and activation. Although crucial for advancing basic immunology and immunotherapy, there is a notable absence of synthetic material toolkits that examine T cells at both levels, and especially those capable of single-molecule-level manipulation. Here we devise a biomimetic antigen-presenting system (bAPS) for single-cell stimulation and ensemble modulation of T-cell recognition. Our bAPS uses hexapod heterostructures composed of a submicrometer cubic hematite core (α-Fe2O3) and nanostructured silica branches with diverse surface modifications. At single-molecule resolution, we show T-cell activation by a single agonist peptide-loaded major histocompatibility complex; distinct T-cell receptor (TCR) responses to structurally similar peptides that differ by only one amino acid; and the superior antigen recognition sensitivity of TCRs compared with that of chimeric antigen receptors (CARs). We also demonstrate how the magnetic field-induced rotation of hexapods amplifies the immune responses in suspended T and CAR-T cells. In addition, we establish our bAPS as a precise and scalable method for identifying stimulatory antigen-specific TCRs at the single-cell level. Thus, our multimodal bAPS represents a unique biointerface tool for investigating T-cell recognition, signaling and function.

T Cell Antigen Recognition and Discrimination by Electrochemiluminescence Imaging

Adoptive T lymphocyte (T cell) transfer and tumour-specific peptide vaccines are innovative cancer therapies. An accurate assessment of the specific reactivity of T cell receptors (TCRs) to tumour antigens is required because of the high heterogeneity of tumour cells and the immunosuppressive tumour microenvironment. In this study, we report a label-free electrochemiluminescence (ECL) imaging approach for recognising and discriminating between TCRs and tumour-specific antigens by imaging the immune synapses of T cells. Various T cell stimuli, including agonistic antibodies, auxiliary molecules, and tumour-specific antigens, were modified on the electrode's surface to allow for their interaction with T cells bearing different TCRs. The formation of immune synapses activated by specific stimuli produced a negative (shadow) ECL image, from which T cell antigen recognition and discrimination were evaluated by analysing the spreading area and the recognition intensity of T cells. This approach provides an easy way to assess TCR-antigen specificity and screen both of them for immunotherapies.

Prediction of protein-ligand binding affinity with deep learning

The prediction of binding affinities between target proteins and small molecule drugs is essential for speeding up the drug research and design process. To attain precise and effective affinity prediction, computer-aided methods are employed in the drug discovery pipeline. In the last decade, a variety of computational methods has been developed, with deep learning being the most commonly used approach. We have gathered several deep learning methods and classified them into convolutional neural networks (CNNs), graph neural networks (GNNs), and Transformers for analysis and discussion. Initially, we conducted an analysis of the different deep learning methods, focusing on their feature construction and model architecture. We discussed the advantages and disadvantages of each model. Subsequently, we conducted experiments using four deep learning methods on the PDBbind v.2016 core set. We evaluated their prediction capabilities in various affinity intervals and statistically and visually analyzed the samples of correct and incorrect predictions for each model. Through visual analysis, we attempted to combine the strengths of the four models to improve the Root Mean Square Error (RMSE) of predicted affinities by 1.6% (reducing the absolute value to 1.101) and the Pearson Correlation Coefficient (R) by 2.9% (increasing the absolute value to 0.894) compared to the current state-of-the-art method. Lastly, we discussed the challenges faced by current deep learning methods in affinity prediction and proposed potential solutions to address these issues.

Cis Interactions of Membrane Receptors and Ligands

Cell-cell communication is critical for the development and function of multicellular organisms. A crucial means by which cells communicate with one another is physical interactions between receptors on one cell and their ligands on a neighboring cell. Trans ligand:receptor interactions activate the receptor, ultimately leading to changes in the fate of the receptor-expressing cells. Such trans signaling is known to be critical for the functions of cells in the nervous and immune systems, among others. Historically, trans interactions are the primary conceptual framework for understanding cell-cell communication. However, cells often coexpress many receptors and ligands, and a subset of these has been reported to interact in cis and profoundly impact cell functions. Cis interactions likely constitute a fundamental, understudied regulatory mechanism in cell biology. Here, I discuss how cis interactions between membrane receptors and ligands regulate immune cell functions, and I also highlight outstanding questions in the field.

Gene modified NK cell line as a powerful tool for evaluation of cloned TCRs for TCR-T cell therapy

T cell receptor-engineered T cell (TCR-T) therapy is anticipated as a next generation-immunotherapy for cancer and recent advances of TCR isolation technology have enabled patient's T cells to express TCRs recognizing multiple combinations of specific peptides and human leukocyte antigens (HLA). However, evaluation processes for the TCR-induced cytotoxicity activity using primary T cells are laborious and time-consuming. In this study, we established a cell line that do not express endogenous TCRs, enabling to generate large numbers of homogeneous cells, and can measure the cytotoxic activity of the isolated TCRs. To this end, we transduced a Natural Killer (NK) cell line with human CD3 molecules and interleukin (IL)-2. The TCR expressing NK cells killed target cells as similarly to TCR-transduced primary T cells and secreted various cytokines/chemokines including IL-2. Thus, the gene-modified NK cell can be a powerful tool to rapidly and efficiently evaluate the functions of isolated TCRs.