To understand the dynamic nature of the genome, the localization and rearrangement of DNA and DNA-binding proteins must be analyzed across the entire nucleus of single living cells. Recently, we developed a computational light microscopy technique, called high-resolution diffusion (Hi-D) mapping, which can accurately detect, classify and map diffusion dynamics and biophysical parameters such as the diffusion constant, the anomalous exponent, drift velocity and model physical diffusion from the data at a high spatial resolution across the genome in living cells. Hi-D combines dense optical flow to detect and track local chromatin and nuclear protein motion genome-wide and Bayesian inference to characterize this local movement at nanoscale resolution. Here we present the Python implementation of Hi-D, with an option for parallelizing the calculations to run on multicore central processing units (CPUs). The functionality of Hi-D is presented to the users via user-friendly documented Python notebooks. Hi-D reduces the analysis time to less than 1 h using a multicore CPU with a single compute node. We also present different applications of Hi-D for live-imaging of DNA, histone H2B and RNA polymerase II sequences acquired with spinning disk confocal and super-resolution structured illumination microscopy.

Gene transcription by RNA polymerase II (RNAPol II) is a tightly regulated process in the genomic, temporal, and spatial context. Recently, we have shown that chromatin exhibits spatially coherently moving regions over the entire nucleus, which is enhanced by transcription. Yet, it remains unclear how the mobility of RNA Pol II molecules is affected by transcription regulation and whether this response depends on the coordinated chromatin movement. We applied our Dense Flow reConstruction and Correlation method to analyze nucleus-wide coherent movements of RNA Pol II in living human cancer cells. We observe a spatially coherent movement of RNA Pol II molecules over (Formula presented.) 1 μm, which depends on transcriptional activity. Inducing transcription in quiescent cells decreased the coherent motion of RNA Pol II. We then quantify the spatial correlation length of RNA Pol II in the context of DNA motion. RNA Pol II and chromatin spatially coherent motions respond oppositely to transcriptional activities. Our study holds the potential of studying the chromatin environment in different nuclear processes.

Bulk chromatin motion has not been analyzed at high resolution. We present Hi-D, a method to quantitatively map dynamics of chromatin and abundant nuclear proteins for every pixel simultaneously over the entire nucleus from fluorescence image series. Hi-D combines reconstruction of chromatin motion and classification of local diffusion processes by Bayesian inference. We show that DNA dynamics in the nuclear interior are spatially partitioned into 0.3-3-μm domains in a mosaic-like pattern, uncoupled from chromatin compaction. This pattern was remodeled in response to transcriptional activity. Hi-D can be applied to any dense and bulk structures opening new perspectives towards understanding motion of nuclear molecules.

The eukaryotic genome is hierarchically structured yet highly dynamic. Regulating transcription in this environment demands a high level of coordination to permit many proteins to interact with chromatin fiber at appropriate sites in a timely manner. We describe how recent advances in quantitative imaging techniques overcome caveats of sequencing-based methods (Hi-C and related) by enabling direct visualization of transcription factors and chromatin at high resolution, from single genes to the whole nucleus. We discuss the contribution of fluorescence imaging to deciphering the principles underlying this coordination within the crowded nuclear space in living cells and discuss challenges ahead.

Chromatin ‘blobs’ were recently identified by live super-resolution imaging of labeled nucleosomes as pervasive but fleeting structural entities. However, the mechanisms leading to the formation of these blobs and their functional implications are unknown. We explore here whether causal relationships exist between parameters that characterize the chromatin blob dynamics and structure, by adapting a framework for spatio-temporal Granger-causality inference. Our analysis reveals that chromatin dynamics is a key determinant for both blob area and local density. Such causality, however, could be demonstrated only in 10–20% of the nucleus, suggesting that chromatin dynamics and structure at the nanometer scale are dominated by stochasticity. We show that the theory of active semiflexible polymers can be invoked to provide potential mechanisms leading to the organization of chromatin into blobs. Our results represent a first step toward elucidating the mechanisms that govern the dynamic and stochastic organization of chromatin in the cell nucleus.

Chromatin conformation regulates gene expression and thus, constant remodeling of chromatin structure is essential to guarantee proper cell function. To gain insight into the spatiotemporal organization of the genome, we use high-density photoactivated localization microscopy and deep learning to obtain temporally resolved super-resolution images of chromatin in living cells. In combination with high-resolution dense motion reconstruction, we find elongated ∼45- to 90-nm-wide chromatin "blobs."A computational chromatin model suggests that these blobs are dynamically associating chromatin fragments in close physical and genomic proximity and adopt topologically associated domain-like interactions in the time-average limit. Experimentally, we found that chromatin exhibits a spatiotemporal correlation over ∼4 μm in space and tens of seconds in time, while chromatin dynamics are correlated over ∼6 μm and last 40 s. Notably, chromatin structure and dynamics are closely related, which may constitute a mechanism to grant access to regions with high local chromatin concentration.

Intrinsic dynamics of chromatin contribute to gene regulation. How chromatin mobility responds to genomic processes, and whether this response relies on coordinated chromatin movement is still unclear. Here, we introduce an approach called Dense Flow reConstruction and Correlation (DFCC), to quantify correlation of chromatin motion with sub-pixel sensitivity at the level of the whole nucleus. DFCC reconstructs dense global flowfields of fluorescent images acquired in real-time.We applied our approach to analyze stochastic movements of DNA and histones, based on direction and magnitude at different time lags in human cells. We observe long-range correlations extending over several μm between coherently moving regions over the entire nucleus. Spatial correlation of global chromatin dynamics was reduced by inhibiting elongation by RNA polymerase II, and abolished in quiescent cells. Furthermore, quantification of spatial smoothness over time intervals up to 30 s points to clear-cut boundaries between distinct regions, while smooth transitions in small (<1 μm) neighborhoods dominate for short time intervals. Rough transitions between regions of coherent motion indicate directed squeezing or stretching of chromatin boundaries, suggestive of changes in local concentrations of actors regulating gene expression. The DFCC approach hence allows characterizing stochastically forming domains of nuclear activity.