Single-Molecule Pull-Down FRET to Dissect the Mechanisms of Biomolecular Machines

Single-molecule analysis reveals that a glucagon-bound extracellular domain of the glucagon receptor is dynamic

Dynamic information is vital to understanding the activation mechanism of G protein-coupled receptors (GPCRs). Despite the availability of high-resolution structures of different conformational states, the dynamics of those states at the molecular level are poorly understood. Here, we used total internal reflection fluorescence microscopy to study the extracellular domain (ECD) of the glucagon receptor (GCGR), a class B family GPCR that controls glucose homeostasis. Single-molecule fluorescence resonance energy transfer was used to observe the ECD dynamics of GCGR molecules expressed and purified from mammalian cells. We observed that for apo-GCGR, the ECD is dynamic and spent time predominantly in a closed conformation. In the presence of glucagon, the ECD is wide open and also shows more dynamic behavior than apo-GCGR, a finding that was not previously reported. These results suggest that both apo-GCGR and glucagon-bound GCGRs show reversible opening and closing of the ECD with respect to the seven-transmembrane (7TM) domain. This work demonstrates a molecular approach to visualizing the dynamics of the GCGR ECD and provides a foundation for understanding the conformational changes underlying GPCR activation, which is critical in the development of new therapeutics.

Coming Together: RNAs and Proteins Assemble under the Single-Molecule Fluorescence Microscope

RNAs, across their numerous classes, often work in concert with proteins in RNA-protein complexes (RNPs) to execute critical cellular functions. Ensemble-averaging methods have been instrumental in revealing many important aspects of these RNA-protein interactions, yet are insufficiently sensitive to much of the dynamics at the heart of RNP function. Single-molecule fluorescence microscopy (SMFM) offers complementary, versatile tools to probe RNP conformational and compositional changes in detail. In this review, we first outline the basic principles of SMFM as applied to RNPs, describing key considerations for labeling, imaging, and quantitative analysis. We then sample applications of in vitro and in vivo single-molecule visualization using the case studies of pre-messenger RNA (mRNA) splicing and RNA silencing, respectively. After discussing specific insights single-molecule fluorescence methods have yielded, we briefly review recent developments in the field and highlight areas of anticipated growth.

Life under the Microscope: Single-Molecule Fluorescence Highlights the RNA World

The emergence of single-molecule (SM) fluorescence techniques has opened up a vast new toolbox for exploring the molecular basis of life. The ability to monitor individual biomolecules in real time enables complex, dynamic folding pathways to be interrogated without the averaging effect of ensemble measurements. In parallel, modern biology has been revolutionized by our emerging understanding of the many functions of RNA. In this comprehensive review, we survey SM fluorescence approaches and discuss how the application of these tools to RNA and RNA-containing macromolecular complexes in vitro has yielded significant insights into the underlying biology. Topics covered include the three-dimensional folding landscapes of a plethora of isolated RNA molecules, their assembly and interactions in RNA-protein complexes, and the relation of these properties to their biological functions. In all of these examples, the use of SM fluorescence methods has revealed critical information beyond the reach of ensemble averages.

Defective Ribonucleoproteins, Mistakes in RNA Processing, and Diseases

Ribonucleoproteins (RNPs) are vital to many cellular events. To this end, many neurodegenerative diseases and cancers have been linked to RNP malfunction, particularly as this relates to defective processing of cellular RNA. The connection of RNPs and diseases has also propagated a shift of focus onto RNA targeting from traditional protein targeting treatments. However, therapeutic development in this area has been limited by incomplete molecular insight into the specific contributions of RNPs to disease. This review outlines the role of several RNPs in diseases, focusing on molecular defects in processes that affect proper RNA handling in the cell. This work also evaluates the contributions of recently developed methods to understanding RNP association and function. We review progress in this area by focusing on molecular malfunctions of RNPs associated with the onset and progression of several neurodegenerative diseases and cancer and conclude with a brief discussion of RNA-based therapeutic efforts.

Putting Humpty-Dumpty Together: Clustering the Functional Dynamics of Single Biomolecular Machines Such as the Spliceosome

The spliceosome is a biomolecular machine that, in all eukaryotes, accomplishes site-specific splicing of introns from precursor messenger RNAs (pre-mRNAs) with high fidelity. Operating at the nanometer scale, where inertia and friction have lost the dominant role they play in the macroscopic realm, the spliceosome is highly dynamic and assembles its active site around each pre-mRNA anew. To understand the structural dynamics underlying the molecular motors, clocks, and ratchets that achieve functional accuracy in the yeast spliceosome (a long-standing model system), we have developed single-molecule fluorescence resonance energy transfer (smFRET) approaches that report changes in intra- and intermolecular interactions in real time. Building on our work using hidden Markov models (HMMs) to extract kinetic and conformational state information from smFRET time trajectories, we recognized that HMM analysis of individual state transitions as independent stochastic events is insufficient for a biomolecular machine as complex as the spliceosome. In this chapter, we elaborate on the recently developed smFRET-based Single-Molecule Cluster Analysis (SiMCAn) that dissects the intricate conformational dynamics of a pre-mRNA through the splicing cycle in a model-free fashion. By leveraging hierarchical clustering techniques developed for Bioinformatics, SiMCAn efficiently analyzes large datasets to first identify common molecular behaviors. Through a second level of clustering based on the abundance of dynamic behaviors exhibited by defined functional intermediates that have been stalled by biochemical or genetic tools, SiMCAn then efficiently assigns pre-mRNA FRET states and transitions to specific splicing complexes, with the potential to find heretofore undescribed conformations. SiMCAn thus arises as a general tool to analyze dynamic cellular machines more broadly.

Single-molecule pull-down for investigating protein-nucleic acid interactions

The genome and transcriptome are constantly modified by proteins in the cell. Recent advances in single-molecule techniques allow for high spatial and temporal observations of these interactions between proteins and nucleic acids. However, due to the difficulty of obtaining functional protein complexes, it remains challenging to study the interactions between macromolecular protein complexes and nucleic acids. Here, we combined single-molecule fluorescence with various protein complex pull-down techniques to determine the function and stoichiometry of ribonucleoprotein complexes. Through the use of three examples of protein complexes from eukaryotic cells (Drosha, Dicer, and TUT4 protein complexes), we provide step-by-step guidance for using novel single-molecule techniques. Our single-molecule methods provide sub-second and nanometer resolution and can be applied to other nucleoprotein complexes that are essential for cellular processes.