The presumptive altered dynamics of transient molecular interactions in vivo contributing to neurodegenerative diseases have remained elusive. Here, using single-molecule localization microscopy, we show that disease-inducing Huntingtin (mHtt) protein fragments display three distinct dynamic states in living cells - 1) fast diffusion, 2) dynamic clustering and 3) stable aggregation. Large, stable aggregates of mHtt exclude chromatin and form 'sticky' decoy traps that impede target search processes of key regulators involved in neurological disorders. Functional domain mapping based on super-resolution imaging reveals an unexpected role of aromatic amino acids in promoting protein-mHtt aggregate interactions. Genome-wide expression analysis and numerical simulation experiments suggest mHtt aggregates reduce transcription factor target site sampling frequency and impair critical gene expression programs in striatal neurons. Together, our results provide insights into how mHtt dynamically forms aggregates and disrupts the finely-balanced gene control mechanisms in neuronal cells.

Animal development is orchestrated by spatio-temporal gene expression programmes that drive precise lineage commitment, proliferation and migration events at the single-cell level, collectively leading to large-scale morphological change and functional specification in the whole organism. Efforts over decades have uncovered two 'seemingly contradictory' mechanisms in gene regulation governing these intricate processes: (i) stochasticity at individual gene regulatory steps in single cells and (ii) highly coordinated gene expression dynamics in the embryo. Here we discuss how these two layers of regulation arise from the molecular and the systems level, and how they might interplay to determine cell fate and to control the complex body plan. We also review recent technological advancements that enable quantitative analysis of gene regulation dynamics at single-cell, single-molecule resolution. These approaches outline next-generation experiments to decipher general principles bridging gaps between molecular dynamics in single cells and robust gene regulations in the embryo.

Probing the architecture, mechanism, and dynamics of genome folding is fundamental to our understanding of genome function in homeostasis and disease. Most chromosome conformation capture studies dissect the genome architecture with population- and time-averaged snapshots and thus have limited capabilities to reveal 3D nuclear organization and dynamics at the single-cell level. Here, we discuss emerging imaging techniques ranging from light microscopy to electron microscopy that enable investigation of genome folding and dynamics at high spatial and temporal resolution. Results from these studies complement genomic data, unveiling principles underlying the spatial arrangement of the genome and its potential functional links to diverse biological activities in the nucleus.

Enhancer-binding pluripotency regulators (Sox2 and Oct4) play a seminal role in embryonic stem (ES) cell-specific gene regulation. Here, we combine in vivo and in vitro single-molecule imaging, transcription factor (TF) mutagenesis, and ChIP-exo mapping to determine how TFs dynamically search for and assemble on their cognate DNA target sites. We find that enhanceosome assembly is hierarchically ordered with kinetically favored Sox2 engaging the target DNA first, followed by assisted binding of Oct4. Sox2/Oct4 follow a trial-and-error sampling mechanism involving 84-97 events of 3D diffusion (3.3-3.7 s) interspersed with brief nonspecific collisions (0.75-0.9 s) before acquiring and dwelling at specific target DNA (12.0-14.6 s). Sox2 employs a 3D diffusion-dominated search mode facilitated by 1D sliding along open DNA to efficiently locate targets. Our findings also reveal fundamental aspects of gene and developmental regulation by fine-tuning TF dynamics and influence of the epigenome on target search parameters.

Lipid droplets (LDs) are neutral lipid storage organelles that transfer lipids to various organelles including peroxisomes. Here, we show that the hereditary spastic paraplegia protein M1 Spastin, a membrane-bound AAA ATPase found on LDs, coordinates fatty acid (FA) trafficking from LDs to peroxisomes through two inter-related mechanisms. First, M1 Spastin forms a tethering complex with peroxisomal ABCD1 to promote LD-peroxisome contact formation. Second, M1 Spastin recruits the membrane-shaping ESCRT-III proteins IST1 and CHMP1B to LDs via its MIT domain to facilitate LD-to-peroxisome FA trafficking, possibly through IST1 and CHMP1B modifying LD membrane morphology. Furthermore, M1 Spastin, IST1 and CHMP1B are all required to relieve LDs of lipid peroxidation. The roles of M1 Spastin in tethering LDs to peroxisomes and in recruiting ESCRT-III components to LD-peroxisome contact sites for FA trafficking may help explain the pathogenesis of diseases associated with defective FA metabolism in LDs and peroxisomes.

Deconstructing the mechanism by which the 3D genome encodes genetic information to generate diverse cell types during animal development is a major challenge in biology. The contrast between the elimination of chromatin loops and domains upon Cohesin loss and the lack of downstream gene expression changes at the cell population level instigates intense debates regarding the structure-function relationship between genome organization and gene regulation. Here, by analyzing single cells after acute Cohesin removal with sequencing and spatial genome imaging techniques, we discover that, instead of dictating population-wide gene expression levels, 3D genome topology mediated by Cohesin safeguards long-range gene co-expression correlations in single cells. Notably, Cohesin loss induces gene co-activation and chromatin co-opening between active domains in cis up to tens of megabase apart, far beyond the typical length scale of enhancer-promoter communication. In addition, Cohesin separates Mediator protein hubs, prevents active genes in cis from localizing into shared hubs and blocks intersegment transfer of diverse transcriptional regulators. Together, these results support that spatial organization of the 3D genome orchestrates dynamic long-range gene and chromatin co-regulation in single living cells.

Our ability to unambiguously image and track individual molecules in live cells is limited by packing of multiple copies of labeled molecules within the resolution limit. Here we devise a universal genetic strategy to precisely control protein copy number in a cell. This system has a dynamic titration range of more than 10,000 fold, enabling sparse labeling of proteins expressed at widely different levels. Combined with fluorescence signal amplification tags, this system extends the duration of automated single-molecule tracking by 2 orders of magnitude. We demonstrate long-term imaging of synaptic vesicle dynamics in cultured neurons as well as in live zebrafish. We found that axon initial segment utilizes a waterfall mechanism gating synaptic vesicle transport polarity by promoting anterograde transport processivity. Long-time observation also reveals that transcription factor Sox2 samples clustered binding sites in spatially-restricted sub-nuclear regions, suggesting that topological structures in the nucleus shape local gene activities by a sequestering mechanism. This strategy thus greatly expands the spatiotemporal length scales of live-cell single-molecule measurements for a quantitative understanding of complex control of molecular dynamics in vivo.

Oncogene amplification on extrachromosomal DNA (ecDNA) is a common event, driving aggressive tumor growth, drug resistance and shorter survival. Currently, the impact of nonchromosomal oncogene inheritance-random identity by descent-is poorly understood. Also unclear is the impact of ecDNA on somatic variation and selection. Here integrating theoretical models of random segregation, unbiased image analysis, CRISPR-based ecDNA tagging with live-cell imaging and CRISPR-C, we demonstrate that random ecDNA inheritance results in extensive intratumoral ecDNA copy number heterogeneity and rapid adaptation to metabolic stress and targeted treatment. Observed ecDNAs benefit host cell survival or growth and can change within a single cell cycle. ecDNA inheritance can predict, a priori, some of the aggressive features of ecDNA-containing cancers. These properties are facilitated by the ability of ecDNA to rapidly adapt genomes in a way that is not possible through chromosomal oncogene amplification. These results show how the nonchromosomal random inheritance pattern of ecDNA contributes to poor outcomes for patients with cancer.

Enzymatic probes of chromatin structure reveal accessible versus inaccessible chromatin states, while super-resolution microscopy reveals a continuum of chromatin compaction states. Characterizing histone H2B movements by single-molecule tracking (SMT), we resolved chromatin domains ranging from low to high mobility and displaying different subnuclear localizations patterns. Heterochromatin constituents correlated with the lowest mobility chromatin, whereas transcription factors varied widely with regard to their respective mobility with low- or high-mobility chromatin. Pioneer transcription factors, which bind nucleosomes, can access the low-mobility chromatin domains, whereas weak or non-nucleosome binding factors are excluded from the domains and enriched in higher mobility domains. Nonspecific DNA and nucleosome binding accounted for most of the low mobility of strong nucleosome interactor FOXA1. Our analysis shows how the parameters of the mobility of chromatin-bound factors, but not their diffusion behaviors or SMT-residence times within chromatin, distinguish functional characteristics of different chromatin-interacting proteins.

This protocol provides a two-parameter analysis of single-molecule tracking (SMT) trajectories of Halo-tagged histones in living adherent cell lines and unveils a chromatin mobility landscape composed of five chromatin types, ranging from low to high mobility. When the analysis is applied to Halo-tagged, chromatin-binding proteins, it associates chromatin interaction properties with known functions in a way that previously used SMT parameters did not. For complete information on the use and execution of this protocol, please refer to Lerner et al. (2020).