Bridging the Nanoscopy-Immunology Gap

Abstract

Bridging the gap between traditional immunology and nanoscale biophysics has proved more difficult than originally thought. For cell biology applications however, super-resolution microscopy has already facilitated considerable advances. From neuronal segmentation to nuclear pores and 3D focal adhesion structure-nanoscopy has begun to illuminate links between nanoscale organization and function. With immunology, the explanation must go further, relating nanoscale biophysical phenomena to the manifestation of specific diseases, or the altered activity of specific immune cell types in a bodily compartment. What follows is a summary of how nanoscopy has elucidated single cell immunological function, and what might be achieved in the future to link quantifiable, nanoscale, biophysical phenomena with cell and whole tissue functionality. We explore where the gaps in our understanding occur, and how they might be addressed.

Differential nanoscale organisation of LFA-1 modulates T-cell migration

“…Determining what are the live-cell dynamics and rare events that occur in the regulation of nanoclusters will be key to understanding how cells use spatiotemporal molecular organisation to change their behaviour. New high-throughput techniques (Holden et al, 2014;Gunkel et al, 2014;Yasui et al, 2018) to low-power imaging (Chen et al, 2014) and new fluorescent proteins (Zhang et al, 2016;Chang et al, 2012;Tiwari et al, 2015) may soon enable these kind of investigations, and will be especially important in connecting nanoscale regulation to whole-cell function in diverse settings (Shannon and Owen, 2019), including in autoimmune disease.…”

Differential nanoscale organisation of LFA-1 modulates T cell migration

“…The question of live cell dynamics and rare events in the regulation of nanoclusters will be key to understanding how cells use spatiotemporal molecular organisation to change their behaviour. New high throughput techniques (Holden et al 2014;Gunkel et al 2014) coupled to low power imaging (Chen et al 2014), and new fluorescent proteins (Zhang et al 2016;Chang et al 2012;Tiwari et al 2015) may soon enable these kind of investigations, and will be especially important in connecting nanoscale regulation to whole cell function in diverse settings (Shannon & Owen 2019), including in autoimmune disease.…”

Divide and Conquer: Real-time maximum likelihood fitting of multiple emitters for super-resolution localization microscopy

“…The image analysis speed is preferable to be real-time, so that the acquisition parameters can be optimized during SRLM experiments [11][12][13]. Note that high imaging throughput and realtime acquisition optimization are both required for applying SRLM in high-throughput or high-content imaging of a large cell population [5,11,14,15], which are currently used to reduce selection bias, reveal cell-to-cell differences, and discover rare phenotypes or events [16,17]. Of course, it would be interesting to investigate how to combine localization algorithms with deep learning to further improve the imaging speed and/or imaging throughput of SRLM, without compromising other requirements from high-throughput localization microscopy.…”