AbstractAutophagy is an evolutionarily conserved process for degradation and recycling of intracellular components. Although autophagy has been extensively studied over the past decades, it still remains unclear how autophagosome formation occurs in response to starvation. Here, using quantitative Photoactivated Localization Microscopy (qPALM) we have analyzed the nanoscopic spatial distribution and the oligomeric states of endogenous ULK1, the central autophagy induction regulator. For this, we introduced the gene of mEos2, a photoswitchable fluorescent protein, into the ULK1 allele of the HeLa cell genome using a genome-editing technique to express mEos2-ULK1 at an endogenous level. With single-molecule sensitivity, we found that ULK1 exists as various oligomers with clustered and arc-shaped structures throughout the cytoplasm. Upon induction of autophagy by amino acid starvation, a small fraction of ULK1 molecules formed higher-order oligomers localized to larger spherical structures with radii up to 380 nm. Cross-correlation analysis of two-color PALM data of ULK1 and its interaction partner Atg13 revealed that ULK1 structures composed of more than ~40 molecules form under starvation only when ULK1 and Atg13 are colocalized. Through two-color PALM analysis of ULK1 and the endoplasmic reticulum (ER) compartment, we found that these autophagic ULK1 structures occur in a close proximity of the ER within 800 nm. These results indicate that ULK1 might engage in the initiation of autophagosome formation at and near the ER where its cluster size expands to contain more than 40 ULK1 molecules. This quantitative analysis of endogenous ULK1 has provided unprecedented insights into the origin of the autophagy initiation structures.Significance StatementDespite extensive research over the past decades, the molecular mechanism for autophagy initiation remains obscure. Here, we applied Photoactivation Localization Microscopy techniques, coupled with genome-editing, to quantify the oligomeric states and nanoscale behaviors of endogenous ULK1, the central autophagy regulator. The quantitative PALM analysis revealed that ULK1 forms high order multimeric clusters containing up to ~60 molecules, and the oligomeric states increase in response to amino acid starvation up to ~190 molecules. Through cross-correlation analysis, we identified a threshold number of ULK1 molecules that might reflect the state of ULK1 engaging in autophagy initiation in close proximity to the endoplasmic reticulum. These results have provided an unprecedented level of insight into the molecular behavior of ULK1 during autophagy initiation.

Single molecule localization microscopy has become a prominent technique to quantitatively study biological processes below the optical diffraction limit. By fitting the intensity profile of single sparsely activated fluorophores, which are often attached to a specific biomolecule within a cell, the locations of all imaged fluorophores are obtained with ∼20 nm resolution in the form of a coordinate table. While rendered super-resolution images reveal structural features of intracellular structures below the optical diffraction limit, the ability to further analyze the molecular coordinates presents opportunities to gain additional quantitative insights into the spatial distribution of a biomolecule of interest. For instance, pair-correlation or radial distribution functions are employed as a measure of clustering, and cross-correlation analysis reveals the colocalization of two biomolecules in two-color SMLM data. Here, we present an efficient filtering method for SMLM data sets based on pair- or cross-correlation to isolate localizations that are clustered or appear in proximity to a second set of localizations in two-color SMLM data. In this way, clustered or colocalized localizations can be separately rendered and analyzed to compare other molecular properties to the remaining localizations, such as their oligomeric state or mobility in live cell experiments. Current matrix-based cross-correlation analyses of large data sets quickly reach the limitations of computer memory due to the space complexity of constructing the distance matrices. Our approach leverages k-dimensional trees to efficiently perform range searches, which dramatically reduces memory needs and the time for the analysis. We demonstrate the versatile applications of this method with simulated data sets as well as examples of two-color SMLM data. The provided MATLAB code and its description can be integrated into existing localization analysis packages and provides a useful resource to analyze SMLM data with new detail.

Spatial light modulation using cost efficient digital micromirror devices (DMD) is finding broad applications in fluorescence microscopy due to the reduction of phototoxicity and bleaching and the ability to manipulate proteins in optogenetic experiments. However, precise illumination by DMDs and their application to single-molecule localization microscopy (SMLM) remained a challenge because of non-linear distortions between the DMD and camera coordinate systems caused by optical components in the excitation and emission path. Here we develop a fast and easy to implement calibration procedure that determines these distortions and matches the DMD and camera coordinate system with a precision below the optical diffraction limit. As a result, a region from a fluorescence image can be selected with a higher precision for illumination compared to a rigid transformation allowed by manual alignment of the DMD. We first demonstrate the application of our precisely calibrated light modulation by performing a proof of concept fluorescence recovery after photobleaching experiment with the endoplasmic reticulum-localized protein IRE1 fused to GFP in budding yeast (S. cerevisiae). Next, we develop a spatially informed photoactivation approach for SMLM in which only regions of the cell that contain photoactivatable fluorescent proteins are selected for photoactivation. The reduced exposure of the cells to 405 nm light increased the possible imaging time by 44% until phototoxic effects cause a dominant fluorescence background and a change in cell morphology. As a result, the mean number of reliable single-molecule localizations was also significantly increased by 28%. Since the localization precision and the ability for single-molecule tracking is not altered compared to traditional photoactivation of the entire field of view, spatially informed photoactivation significantly improves the quality of SMLM images and single-molecule tracking data. Our precise calibration method therefore lays the foundation for improved SMLM with active feedback photoactivation far beyond the applications in this work.

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