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Scientists develop new method to find antigens that trigger specific immune cells faster and more accurately
The secrets of a cell can be revealed from its surface
A team of scientists at Stanford University has developed a new method to more quickly and accurately predict which antigen will trigger a strong immune response
T cells are a type of immune cell that crawls and squeezes past other cells as they patrol the body
"T cells can detect an antigenic peptide among 10,000 to 100,000 non-antigenic peptides on the cell surface," said Fordyce, assistant professor of bioengineering and genetics
The key to selectivity lies in the crawling of T cells
Fordyce said
imitation of cells
Finding the optimal antigen-receptor pair requires simultaneously applying a sliding or shearing force between the peptide and T cells, and measuring T cell activation
Postdoctoral scholar Yinnian Feng, the study's first author, developed a trick that allowed the research team to measure the interaction of 20 unique peptides with thousands of T cells in less than five hours
To create a simplified system that mimics suspended polypeptide cells, they constructed small spherical beads of a material that expands when heated and attaches several molecules of a given polypeptide particle pMHCs to their surfaces
They could run hundreds of separate experiments in parallel by using each unique color-labeled bead, which made it possible to track multiple different pMHCs
In a demonstration of their platform, the research team showed 21 unique peptides, their results confirmed a T cell receptor known to activate and non-activating peptides, and revealed a previously unknown antigen that can induce strong T cellular response
Using their technique, the research team characterized T-cell receptors that can specifically recognize tumor antigens without generating off-target responses
Scientists hope that this method, which is fast and requires very few cells, or an optimized method, could one day be used to improve personalized immunotherapy
Reference: Bead-based method for high-throughput mapping of the sequence- and force-dependence of T cell activation