By providing quantitative, visual data of live cells, fluorescent protein-based microscopy techniques are furnishing novel insights into the complexities of membrane trafficking pathways and organelle dynamics. In this chapter, we describe experimental protocols employing fluorescent protein-based photohighlighting techniques to quantify protein movement into and out of the Golgi apparatus, an organelle that serves as the central sorting and processing station of the secretory pathway. The methods allow kinetic characteristics of Golgi-associated protein trafficking to be deciphered, which can help clarify how the Golgi maintains itself as a steady-state structure despite a continuous flux of secretory cargo passing into and out of this organelle. The guidelines presented in this chapter can also be applied to examine the dynamics of other intracellular organelle systems, elucidating mechanisms for how proteins are maintained in specific organelles and/or circulated to other destinations within the cell.

The stoichiometry and composition of membrane protein receptors are critical to their function. However, the inability to assess receptor subunit stoichiometry in situ has hampered efforts to relate receptor structures to functional states. Here, we address this problem for the asialoglycoprotein receptor using ensemble FRET imaging, analytical modeling, and single-molecule counting with photoactivated localization microscopy (PALM). We show that the two subunits of asialoglycoprotein receptor [rat hepatic lectin 1 (RHL1) and RHL2] can assemble into both homo- and hetero-oligomeric complexes, displaying three forms with distinct ligand specificities that coexist on the plasma membrane: higher-order homo-oligomers of RHL1, higher-order hetero-oligomers of RHL1 and RHL2 with two-to-one stoichiometry, and the homo-dimer RHL2 with little tendency to further homo-oligomerize. Levels of these complexes can be modulated in the plasma membrane by exogenous ligands. Thus, even a simple two-subunit receptor can exhibit remarkable plasticity in structure, and consequently function, underscoring the importance of deciphering oligomerization in single cells at the single-molecule level.

The stoichiometry and composition of membrane protein receptors are critical to their function. However, the inability to assess receptor subunit stoichiometry in situ has hampered efforts to relate receptor structures to functional states. Here, we address this problem for the asialoglycoprotein receptor using ensemble FRET imaging, analytical modeling, and single-molecule counting with photoactivated localization microscopy (PALM). We show that the two subunits of asialoglycoprotein receptor [rat hepatic lectin 1 (RHL1) and RHL2] can assemble into both homo- and hetero-oligomeric complexes, displaying three forms with distinct ligand specificities that coexist on the plasma membrane: higher-order homo-oligomers of RHL1, higher-order hetero-oligomers of RHL1 and RHL2 with two-to-one stoichiometry, and the homo-dimer RHL2 with little tendency to further homo-oligomerize. Levels of these complexes can be modulated in the plasma membrane by exogenous ligands. Thus, even a simple two-subunit receptor can exhibit remarkable plasticity in structure, and consequently function, underscoring the importance of deciphering oligomerization in single cells at the single-molecule level.

Autophagy is an evolutionarily conserved, intracellular self-defense mechanism in which organelles and proteins are sequestered into autophagic vesicles that are subsequently degraded through fusion with lysosomes. Cells, thereby, prevent the toxic accumulation of damaged or unnecessary components, but also recycle these components to sustain metabolic homoeostasis. Heightened autophagy is a mechanism of resistance for cancer cells faced with metabolic and therapeutic stress, revealing opportunities for exploitation as a therapeutic target in cancer. We summarize recent developments in the field of autophagy and cancer and build upon the results presented at the Cancer Therapy Evaluation Program (CTEP) Early Drug Development meeting in March 2010. Herein, we describe our current understanding of the core components of the autophagy machinery and the functional relevance of autophagy within the tumor microenvironment, and we outline how this knowledge has informed preclinical investigations combining the autophagy inhibitor hydroxychloroquine (HCQ) with chemotherapy, targeted therapy, and immunotherapy. Finally, we describe ongoing clinical trials involving HCQ as a first generation autophagy inhibitor, as well as strategies for the development of novel, more potent, and specific inhibitors of autophagy.

Photoactivated localization microscopy (PALM) is a powerful approach for investigating protein organization, yet tools for quantitative, spatial analysis of PALM datasets are largely missing. Combining pair-correlation analysis with PALM (PC-PALM), we provide a method to analyze complex patterns of protein organization across the plasma membrane without determination of absolute protein numbers. The approach uses an algorithm to distinguish a single protein with multiple appearances from clusters of proteins. This enables quantification of different parameters of spatial organization, including the presence of protein clusters, their size, density and abundance in the plasma membrane. Using this method, we demonstrate distinct nanoscale organization of plasma-membrane proteins with different membrane anchoring and lipid partitioning characteristics in COS-7 cells, and show dramatic changes in glycosylphosphatidylinositol (GPI)-anchored protein arrangement under varying perturbations. PC-PALM is thus an effective tool with broad applicability for analysis of protein heterogeneity and function, adaptable to other single-molecule strategies.

Molecular motors in cells typically produce highly directed motion; however, the aggregate, incoherent effect of all active processes also creates randomly fluctuating forces, which drive diffusive-like, nonthermal motion. Here, we introduce force-spectrum-microscopy (FSM) to directly quantify random forces within the cytoplasm of cells and thereby probe stochastic motor activity. This technique combines measurements of the random motion of probe particles with independent micromechanical measurements of the cytoplasm to quantify the spectrum of force fluctuations. Using FSM, we show that force fluctuations substantially enhance intracellular movement of small and large components. The fluctuations are three times larger in malignant cells than in their benign counterparts. We further demonstrate that vimentin acts globally to anchor organelles against randomly fluctuating forces in the cytoplasm, with no effect on their magnitude. Thus, FSM has broad applications for understanding the cytoplasm and its intracellular processes in relation to cell physiology in healthy and diseased states.

The distinctive distributions of proteins within subcellular compartments both at steady state and during signaling events have essential roles in cell function. Here we describe a method for delineating the complex arrangement of proteins within subcellular structures visualized using point-localization superresolution (PL-SR) imaging. The approach, called pair correlation photoactivated localization microscopy (PC-PALM), uses a pair-correlation algorithm to precisely identify single molecules in PL-SR imaging data sets, and it is used to decipher quantitative features of protein organization within subcellular compartments, including the existence of protein clusters and the size, density and number of proteins in these clusters. We provide a step-by-step protocol for PC-PALM, illustrating its analysis capability for four plasma membrane proteins tagged with photoactivatable GFP (PAGFP). The experimental steps for PC-PALM can be carried out in 3 d and the analysis can be done in ∼6-8 h. Researchers need to have substantial experience in single-molecule imaging and statistical analysis to conduct the experiments and carry out this analysis.

Pointillistic based super-resolution techniques, such as photoactivated localization microscopy (PALM), involve multiple cycles of sequential activation, imaging, and precise localization of single fluorescent molecules. A super-resolution image, having nanoscopic structural information, is then constructed by compiling all the image sequences. Because the final image resolution is determined by the localization precision of detected single molecules and their density, accurate image reconstruction requires imaging of biological structures labeled with fluorescent molecules at high density. In such image datasets, stochastic variations in photon emission and intervening dark states lead to uncertainties in identification of single molecules. This, in turn, prevents the proper utilization of the wealth of information on molecular distribution and quantity. A recent strategy for overcoming this problem is pair-correlation analysis applied to PALM. Using rigorous statistical algorithms to estimate the number of detected proteins, this approach allows the spatial organization of molecules to be quantitatively described.