Upon activation via antigen binding, T cell receptors (TCRs) become phosphorylated and cluster, initiating a signalling cascade which ultimately leads to T cell activation. Single-Molecule Localization Microscopy (SMLM) is an essential tool for studying nanoclusters and quantifying the TCR activation pathway, as these events take place at a molecular level beneath the resolution limit of conventional optical microscopes. SMLM achieves high molecular precision by employing switchable fluorescent signals and identifies individual molecules within a diffraction-limited area. Points accumulation in nanoscale topography (PAINT), including DNA-PAINT and protein-PAINT (pPAINT), offers even greater quantification of SMLM data. Unlike traditional SMLM techniques, PAINT is not limited by spectral limitations or bleaching, allowing for more accurate quantification of TCR clustering and molecular organization at the plasma membrane. Here we present a pipeline to analyze PAINT data collected in T cells, using the Picasso software package, to quantify the nanoclusters in activated cells.

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Analyzing Point Accumulation in Nanoscale Topography (PAINT) Data to Decipher T Cell Receptor Cluster Signalling

  • Shirin Ansari,
  • James C. Walsh,
  • Jesse Goyette

摘要

Upon activation via antigen binding, T cell receptors (TCRs) become phosphorylated and cluster, initiating a signalling cascade which ultimately leads to T cell activation. Single-Molecule Localization Microscopy (SMLM) is an essential tool for studying nanoclusters and quantifying the TCR activation pathway, as these events take place at a molecular level beneath the resolution limit of conventional optical microscopes. SMLM achieves high molecular precision by employing switchable fluorescent signals and identifies individual molecules within a diffraction-limited area. Points accumulation in nanoscale topography (PAINT), including DNA-PAINT and protein-PAINT (pPAINT), offers even greater quantification of SMLM data. Unlike traditional SMLM techniques, PAINT is not limited by spectral limitations or bleaching, allowing for more accurate quantification of TCR clustering and molecular organization at the plasma membrane. Here we present a pipeline to analyze PAINT data collected in T cells, using the Picasso software package, to quantify the nanoclusters in activated cells.