Single-molecule tracking (SMT): a window into live-cell transcription biochemistry

Robust Quantification of Live-Cell Single-Molecule Tracking Data for Fluorophores with Different Photophysical Properties

High-speed single-molecule tracking in live cells is becoming an increasingly popular method for quantifying the spatiotemporal behavior of proteins in vivo. The method provides a wealth of quantitative information, but users need to be aware of biases that can skew estimates of molecular mobilities. The range of suitable fluorophores for live-cell single-molecule imaging has grown substantially over the past few years, but it remains unclear to what extent differences in photophysical properties introduce biases. Here, we tested two fluorophores with entirely different photophysical properties, one that photoswitches frequently between bright and dark states (TMR) and one that shows exceptional photostability without photoswitching (JFX650). We used a fusion of the Escherichia coli DNA repair enzyme MutS to the HaloTag and optimized sample preparation and imaging conditions for both types of fluorophore. We then assessed the reliability of two common data analysis algorithms, mean-square displacement (MSD) analysis and Hidden Markov Modeling (HMM), to estimate the diffusion coefficients and fractions of MutS molecules in different states of motion. We introduce a simple approach that removes discrepancies in the data analyses and show that both algorithms yield consistent results, regardless of the fluorophore used. Nevertheless, each dye has its own strengths and weaknesses, with TMR being more suitable for sampling the diffusive behavior of many molecules, while JFX650 enables prolonged observation of only a few molecules per cell. These characterizations and recommendations should help to standardize measurements for increased reproducibility and comparability across studies.

Chromatin structure and dynamics: one nucleosome at a time

Eukaryotic genomes store information on many levels, including their linear DNA sequence, the posttranslational modifications of its constituents (epigenetic modifications), and its three-dimensional folding. Understanding how this information is stored and read requires multidisciplinary collaborations from many branches of science beyond biology, including physics, chemistry, and computer science. Concurrent recent developments in all these areas have enabled researchers to image the genome with unprecedented spatial and temporal resolution. In this review, we focus on what single-molecule imaging and tracking of individual proteins in live cells have taught us about chromatin structure and dynamics. Starting with the basics of single-molecule tracking (SMT), we describe some advantages over in situ imaging techniques and its current limitations. Next, we focus on single-nucleosome studies and what they have added to our current understanding of the relationship between chromatin dynamics and transcription. In celebration of Robert Feulgen's ground-breaking discovery that allowed us to start seeing the genome, we discuss current models of chromatin structure and future challenges ahead.

Real-time single-molecule imaging of transcriptional regulatory networks in living cells

Gene regulatory networks drive the specific transcriptional programmes responsible for the diversification of cell types during the development of multicellular organisms. Although our knowledge of the genes involved in these dynamic networks has expanded rapidly, our understanding of how transcription is spatiotemporally regulated at the molecular level over a wide range of timescales in the small volume of the nucleus remains limited. Over the past few decades, advances in the field of single-molecule fluorescence imaging have enabled real-time behaviours of individual transcriptional components to be measured in living cells and organisms. These efforts are now shedding light on the dynamic mechanisms of transcription, revealing not only the temporal rules but also the spatial coordination of underlying molecular interactions during various biological events.

Surprising Features of Nuclear Receptor Interaction Networks Revealed by Live Cell Single Molecule Imaging

Type 2 Nuclear Receptors (T2NRs) require heterodimerization with a common partner, the Retinoid X Receptor (RXR), to bind cognate DNA recognition sites in chromatin. Based on previous biochemical and over-expression studies, binding of T2NRs to chromatin is proposed to be regulated by competition for a limiting pool of the core RXR subunit. However, this mechanism has not yet been tested for endogenous proteins in live cells. Using single molecule tracking (SMT) and proximity-assisted photoactivation (PAPA), we monitored interactions between endogenously tagged retinoid X receptor (RXR) and retinoic acid receptor (RAR) in live cells. Unexpectedly, we find that higher expression of RAR, but not RXR increases heterodimerization and chromatin binding in U2OS cells. This surprising finding indicates the limiting factor is not RXR but likely its cadre of obligate dimer binding partners. SMT and PAPA thus provide a direct way to probe which components are functionally limiting within a complex TF interaction network providing new insights into mechanisms of gene regulation in vivo with implications for drug development targeting nuclear receptors.

Imaging the binding of MECP2 to DNA

Mutations in the methyl-DNA binding domain of MECP2 cause Rett syndrome; however, distinct mutations are associated with different severity of the disease. Live-cell imaging and single-molecule tracking are sensitive methods to quantify the DNA binding affinity and diffusion dynamics of nuclear proteins. In this issue of Genes & Development, Zhou and colleagues (pp. 883-900) used these imaging methods to quantitatively describe the partial loss of DNA binding resulting from a novel pathological MECP2 mutation with intermediate disease severity. These data demonstrate how single-molecule tracking can advance understanding of the molecular mechanisms connecting MECP2 mutations with Rett syndrome pathophysiology.

From the membrane to the nucleus: mechanical signals and transcription regulation

Mechanical forces drive and modulate a wide variety of processes in eukaryotic cells including those occurring in the nucleus. Relevantly, forces are fundamental during development since they guide lineage specifications of embryonic stem cells. A sophisticated macromolecular machinery transduces mechanical stimuli received at the cell surface into a biochemical output; a key component in this mechanical communication is the cytoskeleton, a complex network of biofilaments in constant remodeling that links the cell membrane to the nuclear envelope. Recent evidence highlights that forces transmitted through the cytoskeleton directly affect the organization of chromatin and the accessibility of transcription-related molecules to their targets in the DNA. Consequently, mechanical forces can directly modulate transcription and change gene expression programs. Here, we will revise the biophysical toolbox involved in the mechanical communication with the cell nucleus and discuss how mechanical forces impact on the organization of this organelle and more specifically, on transcription. We will also discuss how live-cell fluorescence imaging is producing exquisite information to understand the mechanical response of cells and to quantify the landscape of interactions of transcription factors with chromatin in embryonic stem cells. These studies are building new biophysical insights that could be fundamental to achieve the goal of manipulating forces to guide cell differentiation in culture systems.

Multiomics Analysis Reveals Novel Genetic Determinants for Lens Differentiation, Structure, and Transparency

Recent advances in next-generation sequencing and data analysis have provided new gateways for identification of novel genome-wide genetic determinants governing tissue development and disease. These advances have revolutionized our understanding of cellular differentiation, homeostasis, and specialized function in multiple tissues. Bioinformatic and functional analysis of these genetic determinants and the pathways they regulate have provided a novel basis for the design of functional experiments to answer a wide range of long-sought biological questions. A well-characterized model for the application of these emerging technologies is the development and differentiation of the ocular lens and how individual pathways regulate lens morphogenesis, gene expression, transparency, and refraction. Recent applications of next-generation sequencing analysis on well-characterized chicken and mouse lens differentiation models using a variety of omics techniques including RNA-seq, ATAC-seq, whole-genome bisulfite sequencing (WGBS), chip-seq, and CUT&RUN have revealed a wide range of essential biological pathways and chromatin features governing lens structure and function. Multiomics integration of these data has established new gene functions and cellular processes essential for lens formation, homeostasis, and transparency including the identification of novel transcription control pathways, autophagy remodeling pathways, and signal transduction pathways, among others. This review summarizes recent omics technologies applied to the lens, methods for integrating multiomics data, and how these recent technologies have advanced our understanding ocular biology and function. The approach and analysis are relevant to identifying the features and functional requirements of more complex tissues and disease states.