For over a decade fluorescence microscopy has demonstrated the capacity to achieve single-molecule localization accuracies of a few nanometers, well below the ∼200 nm lateral and ∼500 nm axial resolution limit of conventional microscopy. Yet, only the recent development of new fluorescence labeling modalities, the increase in sensitivity of imaging hardware, and the creation of novel image analysis tools allow for the emergence of single-molecule-based super-resolution imaging techniques. Novel methods such as photoactivated localization microscopy and stochastic optical reconstruction microscopy can typically reach a tenfold increase in resolution compared to standard microscopy methods. Their implementation is relatively easy only requiring minimal changes to a conventional wide-field or total internal reflection fluorescence microscope. The recent translation of these two methods into commercial imaging systems has made them further accessible to researchers in biology. However, these methods are still evolving rapidly toward imaging live samples with high temporal resolution and depth. In this review, we recall the roots of single-molecule localization microscopy, summarize major recent developments, and offer perspective on potential applications.

Although imperfect spatial localization in single-molecule object tracking experiments has long been recognized to induce apparent motion in an immobile population of molecules, this effect is often ignored or incorrectly analyzed for mobile molecules. In particular, apparent motion due to positional uncertainty is often incorrectly assigned as a distinct diffusive mode. Here we show that, due to both static and dynamic contributions, positional uncertainty does not introduce a new apparent diffusive mode into trajectories, but instead causes a systematic shift of each measured diffusion coefficient. This shift is relatively simple: a factor of σ2/Δt is added to each diffusion coefficient, where σ is the positional uncertainty length scale and Δt is the time interval between observations. Therefore, by calculating the apparent diffusion coefficients as a function of Δt, it is straightforward to separate the true diffusion coefficients from the effective positional uncertainty. As a concrete demonstration, we apply this approach to the diffusion of the protein fibrinogen adsorbed to a hydrophobic surface, a system that exhibits three distinct modes of diffusion.