Exploiting Temporal Correlation of Fortunate Single Molecules for Background-free Super-resolution Imaging

Imaging cellular organelles with single-molecule precision that is free from false detections and background noise is crucial to understanding biology at the fundamental level. Fortunate molecules hold the key, and the inherent temporal correlation across multiple consecutive frames can be exploited to overcome these limitations for high-quality super-resolution imaging of single molecule aggregates and organelles in a cellular system. The method is expected to benefit fields ranging from optical imaging to disease biology.
High-quality imaging is core to any microscopy system, especially in modern times where a plethora of microscopy techniques are available, ranging from electron to super-resolution microscopy. Given this, a high signal to background noise, and multi-fold improvement in localization precision (equivalent to a large PAR-shift [Rev. Sci. Instrum. 93, 093704, 2022; Sci. Rep. 13, 12561, 2023]) adds tremendous value to single molecule localization microscopy (SMLM). The proposed correlation-based SMLM (corrSMLM) inherits these properties which is primarily due to its ability to detect and recognize molecules with long blinking cycles (also known as fortunate single-molecules). These molecules fluoresce longer and appear on multiple frames during data recording thereby distinguishing them from random noise that are not likely to survive for more than a single frame as observed during experiments.
The technique is used to image single molecules located on sub-cellular organelles (such as actin filaments / tubulin / mitochondria) in fixed transfected NIH3T3 cells. Although the number of recorded frames required for getting enough fortunate molecules is large, the image resolution shows >2.5 improvement and has an impressive SBR of >1.5. This is amazing since the method does not demand specialized sample preparation or extensive image processing, and avoids the need for multiple experimentation. Probably, the biggest advantage is that the corrSMLM does not demand any change to the existing hardware, and is yet able to generate high-quality super-resolved images.
Overall, the new technique delivers more out of standard SMLM by exploiting temporal correlation present in the data and is expected to become an indispensable tool for optical imaging, cell biophysics and disease biology.
Full Report: https://www.nature.com/articles/s42003-024-07153-x
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