A coordinate-based co-localization index to quantify and visualize spatial associations in single-molecule localization microscopy

Visualizing the subcellular distribution of proteins and determining whether specific proteins co-localize is one of the main strategies in determining the organization and potential interactions of protein complexes in biological samples. The development of super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) has tremendously increased the ability to resolve protein distribution at nanometer resolution. As super-resolution imaging techniques are becoming instrumental in revealing novel biological insights, new quantitative approaches that exploit the unique nature of SMLM datasets are required. Here, we present a new, local density-based algorithm to quantify co-localization in dual-color SMLM datasets. We show that this method is broadly applicable and only requires molecular coordinates and their localization precision as inputs. Using simulated point patterns, we show that this method robustly measures the co-localization in dual-color SMLM datasets, independent of localization density, but with high sensitivity towards local enrichments. We further validated our method using SMLM imaging of the microtubule network in epithelial cells and used it to study the spatial association between proteins at neuronal synapses. Together, we present a simple and easy-to-use, but powerful method to analyze the spatial association of molecules in dual-color SMLM datasets

Duplex Labeling and Manipulation of Neuronal Proteins Using Sequential CRISPR/Cas9 Gene Editing

CRISPR/Cas9-mediated knock-in methods enable the labeling of individual endogenous proteins to faithfully determine their spatiotemporal distribution in cells. However, reliable multiplexing of knock-in events in neurons remains challenging because of cross talk between editing events. To overcome this, we developed conditional activation of knock-in expression (CAKE), allowing efficient, flexible, and accurate multiplex genome editing in rat neurons. To diminish cross talk, CAKE is based on sequential, recombinase-driven guide RNA (gRNA) expression to control the timing of genomic integration of each donor sequence. We show that CAKE is broadly applicable to co-label various endogenous proteins, including cytoskeletal proteins, synaptic scaffolds, ion channels and neurotransmitter receptor subunits. To take full advantage of CAKE, we resolved the nanoscale co-distribution of endogenous synaptic proteins using super-resolution microscopy, demonstrating that their co-organization depends on synapse size. Finally, we introduced inducible dimerization modules, providing acute control over synaptic receptor dynamics in living neurons. These experiments highlight the potential of CAKE to reveal new biological insight. Altogether, CAKE is a versatile method for multiplex protein labeling that enables the detection, localization, and manipulation of endogenous proteins in neurons.Significance StatementAccurate localization and manipulation of endogenous proteins is essential to unravel neuronal function. While labeling of individual proteins is achievable with existing gene editing techniques, methods to label multiple proteins in neurons are limiting. We introduce a new CRISPR/Cas9 strategy, CAKE, achieving faithful duplex protein labeling using sequential editing of genes. We use CAKE to visualize the co-localization of essential neuronal proteins, including cytoskeleton components, ion channels and synaptic scaffolds. Using super-resolution microscopy, we demonstrate that the co-organization of synaptic scaffolds and neurotransmitter receptors scales with synapse size. Finally, we acutely modulate the dynamics of synaptic receptors using labeling with inducible dimerization domains. Thus, CAKE mediates accurate duplex endogenous protein labeling and manipulation to address biological questions in neurons

Illuminating the brain: Dissecting synaptic architecture through genome editing

In the brain, billions of specialized cells including neurons and microglia together make the complex neuronal connections fundamental to our ability to direct physical, sensory, social and emotional responses. Advancement in the fundamental understanding of the brain, but more broadly in every aspect of scientific progress, comes with the development of new novel analytical techniques and methodologies. In this thesis, we focused our study on developing and applying novel tools to investigate neuronal architecture at the level of protein organization. To summarize, in chapter 2 we first developed a new CRISPR/Cas9 based strategy to label endogenous proteins in neurons. We further expanded on this technique in chapter 3, allowing for duplex labeling and manipulation of multiple endogenous proteins. Second, we described a protocol for single-molecule localization microscopy important for studying protein organization at a sub-micrometer scale (chapter 4), and developed a new analytic method to analyze co-localization in dual-color SMLM datasets (chapter 5). Third, we used the techniques developed in the preceding chapters to study the synaptic organization of AMPAR – auxiliary proteins (chapter 6), and studied the role of the N-terminal domain (NTD) of the AMPAR in synaptic anchoring (chapter 7)

Illuminating the brain: Dissecting synaptic architecture through genome editing

In the brain, billions of specialized cells including neurons and microglia together make the complex neuronal connections fundamental to our ability to direct physical, sensory, social and emotional responses. Advancement in the fundamental understanding of the brain, but more broadly in every aspect of scientific progress, comes with the development of new novel analytical techniques and methodologies. In this thesis, we focused our study on developing and applying novel tools to investigate neuronal architecture at the level of protein organization. To summarize, in chapter 2 we first developed a new CRISPR/Cas9 based strategy to label endogenous proteins in neurons. We further expanded on this technique in chapter 3, allowing for duplex labeling and manipulation of multiple endogenous proteins. Second, we described a protocol for single-molecule localization microscopy important for studying protein organization at a sub-micrometer scale (chapter 4), and developed a new analytic method to analyze co-localization in dual-color SMLM datasets (chapter 5). Third, we used the techniques developed in the preceding chapters to study the synaptic organization of AMPAR – auxiliary proteins (chapter 6), and studied the role of the N-terminal domain (NTD) of the AMPAR in synaptic anchoring (chapter 7)

Single-Molecule Localization Microscopy of Subcellular Protein Distribution in Neurons

Over the past years several forms of superresolution fluorescence microscopy have been developed that offer the possibility to study cellular structures and protein distribution at a resolution well below the diffraction limit of conventional fluorescence microscopy (<200 nm). A particularly powerful superresolution technique is single-molecule localization microscopy (SMLM). SMLM enables the quantitative investigation of subcellular protein distribution at a spatial resolution up to tenfold higher than conventional imaging, even in live cells. Not surprisingly, SMLM has therefore been used in many applications in biology, including neuroscience. This chapter provides a step-by-step SMLM protocol to visualize the nanoscale organization of endogenous proteins in dissociated neurons but can be extended to image other adherent cultured cells. We outline a number of methods to visualize endogenous proteins in neurons for live-cell and fixed application, including immunolabeling, the use of intrabodies for live-cell SMLM, and endogenous tagging using CRISPR/Cas9

A coordinate-based co-localization index to quantify and visualize spatial associations in single-molecule localization microscopy

Visualizing the subcellular distribution of proteins and determining whether specific proteins co-localize is one of the main strategies in determining the organization and potential interactions of protein complexes in biological samples. The development of super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) has tremendously increased the ability to resolve protein distribution at nanometer resolution. As super-resolution imaging techniques are becoming instrumental in revealing novel biological insights, new quantitative approaches that exploit the unique nature of SMLM datasets are required. Here, we present a new, local density-based algorithm to quantify co-localization in dual-color SMLM datasets. We show that this method is broadly applicable and only requires molecular coordinates and their localization precision as inputs. Using simulated point patterns, we show that this method robustly measures the co-localization in dual-color SMLM datasets, independent of localization density, but with high sensitivity towards local enrichments. We further validated our method using SMLM imaging of the microtubule network in epithelial cells and used it to study the spatial association between proteins at neuronal synapses. Together, we present a simple and easy-to-use, but powerful method to analyze the spatial association of molecules in dual-color SMLM datasets

Single-Molecule Localization Microscopy of Subcellular Protein Distribution in Neurons

Over the past years several forms of superresolution fluorescence microscopy have been developed that offer the possibility to study cellular structures and protein distribution at a resolution well below the diffraction limit of conventional fluorescence microscopy (&lt;200 nm). A particularly powerful superresolution technique is single-molecule localization microscopy (SMLM). SMLM enables the quantitative investigation of subcellular protein distribution at a spatial resolution up to tenfold higher than conventional imaging, even in live cells. Not surprisingly, SMLM has therefore been used in many applications in biology, including neuroscience. This chapter provides a step-by-step SMLM protocol to visualize the nanoscale organization of endogenous proteins in dissociated neurons but can be extended to image other adherent cultured cells. We outline a number of methods to visualize endogenous proteins in neurons for live-cell and fixed application, including immunolabeling, the use of intrabodies for live-cell SMLM, and endogenous tagging using CRISPR/Cas9

A Phytochrome-Derived Photoswitch for Intracellular Transport

Cells depend on the proper positioning of their organelles, suggesting that active manipulation of organelle positions can be used to explore spatial cell biology and to restore cellular defects caused by organelle misplacement. Recently, blue-light dependent recruitment of specific motors to selected organelles has been shown to alter organelle motility and positioning, but these approaches lack rapid and active reversibility. The light-dependent interaction of phytochrome B with its interacting factors has been shown to function as a photoswitch, dimerizing under red light and dissociating under far-red light. Here we engineer phytochrome domains into photoswitches for intracellular transport that enable the reversible interaction between organelles and motor proteins. Using patterned illumination and live-cell imaging, we demonstrate that this system provides unprecedented spatiotemporal control. We also demonstrate that it can be used in combination with a blue-light dependent system to independently control the positioning of two different organelles. Precise optogenetic control of organelle motility and positioning will provide a better understanding of and control over the spatial biology of cells

Duplex Labeling and Manipulation of Neuronal Proteins Using Sequential CRISPR/Cas9 Gene Editing

CRISPR/Cas9-mediated knock-in methods enable the labeling of individual endogenous proteins to faithfully determine their spatiotemporal distribution in cells. However, reliable multiplexing of knock-in events in neurons remains challenging because of cross talk between editing events. To overcome this, we developed conditional activation of knock-in expression (CAKE), allowing efficient, flexible, and accurate multiplex genome editing. To diminish cross talk, CAKE is based on sequential, recombinase-driven guide RNA (gRNA) expression to control the timing of genomic integration of each donor sequence. We show that CAKE is broadly applicable in rat neurons to co-label various endogenous proteins, including cytoskeletal proteins, synaptic scaffolds, ion channels and neurotransmitter receptor subunits. To take full advantage of CAKE, we resolved the nanoscale co-distribution of endogenous synaptic proteins using super-resolution microscopy, demonstrating that their coorganization correlates with synapse size. Finally, we introduced inducible dimerization modules, providing acute control over synaptic receptor dynamics in living neurons. These experiments highlight the potential of CAKE to reveal new biological insight. Altogether, CAKE is a versatile method for multiplex protein labeling that enables the detection, localization, and manipulation of endogenous proteins in neurons

ORANGE: A CRISPR/Cas9-based genome editing toolbox for epitope tagging of endogenous proteins in neurons.

The correct subcellular distribution of proteins establishes the complex morphology and function of neurons. Fluorescence microscopy techniques are invaluable to investigate subcellular protein distribution, but they suffer from the limited ability to efficiently and reliably label endogenous proteins with fluorescent probes. We developed ORANGE: Open Resource for the Application of Neuronal Genome Editing, which mediates targeted genomic integration of epitope tags in rodent dissociated neuronal culture, in organotypic slices, and in vivo. ORANGE includes a knock-in library for in-depth investigation of endogenous protein distribution, viral vectors, and a detailed two-step cloning protocol to develop knock-ins for novel targets. Using ORANGE with (live-cell) superresolution microscopy, we revealed the dynamic nanoscale organization of endogenous neurotransmitter receptors and synaptic scaffolding proteins, as well as previously uncharacterized proteins. Finally, we developed a mechanism to create multiple knock-ins in neurons, mediating multiplex imaging of endogenous proteins. Thus, ORANGE enables quantification of expression, distribution, and dynamics for virtually any protein in neurons at nanoscale resolution