Spectroscopic super-resolution fluorescence cell imaging using ultra-small Ge quantum dots

TL;DR

This paper introduces a spectral imaging super-resolution microscopy technique utilizing ultra-small Ge quantum dots, achieving significantly improved localization resolution and faster imaging speeds compared to traditional methods.

Contribution

The study presents a novel spectral imaging approach with ultra-small Ge quantum dots and a new Gaussian fitting algorithm, enabling higher resolution and faster data acquisition in super-resolution microscopy.

Findings

Achieved ~40 nm localization resolution with commercial QDs.

Achieved ~12 nm localization resolution with Ge QDs.

Potential for millisecond-scale data acquisition in live imaging.

Abstract

In single molecule localisation super-resolution microscopy the need for repeated image capture limits the imaging speed, while the size of fluorescence probes limits the possible theoretical localisation resolution. Here, we demonstrated a spectral imaging based super-resolution approach by separating the overlapping diffraction spots into several detectors during a single scanning period and taking advantage of the size-dependent emission wavelength in nanoparticles. This approach has been tested using off-the-shelf quantum dots (Qdot) and in-house novel ultra-small (~3 nm) Ge QDs. Furthermore, we developed a method-specific Gaussian fitting and maximum likelihood estimation based on a Matlab algorithm for fast QDs localisation. We demonstrate that this methodology results in ~ 40 nm localisation resolution using commercial QDs and ~12 nm localisation resolution using Ge QDs. Using a standard scanning confocal microscope we achieved data acquisition rate of 1.6 seconds/frame. However, we show that this approach has a potential to deliver data acquisition rates on ms scale thus providing super-resolution in live systems.