Nuclear dynamics of radiation-induced foci in euchromatin and heterochromatin

Abstract

Repair of double strand breaks (DSBs) is essential for cell survival and genome integrity. While much is known about the molecular mechanisms involved in DSB repair and checkpoint activation, the roles of nuclear dynamics of radiation-induced foci (RIF) in DNA repair are just beginning to emerge. Here, we summarize results from recent studies that point to distinct features of these dynamics in two different chromatin environments: heterochromatin and euchromatin. We also discuss how nuclear architecture and chromatin components might control these dynamics, and the need of novel quantification methods for a better description and interpretation of these phenomena. These studies are expected to provide new biomarkers for radiation risk and new strategies for cancer detection and treatment.

Keywords: Biomarker; Cancer risk; Chromatin dynamics; DSB response; Ionizing radiation; Modeling.

Figure 1

γH2AX RIF move from heterochromatin to euchromatin in mouse cells. Immunofluorescence analysis [11] of Balb/C mouse cells show that γH2AX RIF (red) are mostly excluded from the heterochromatic domains (DAPI-bright regions, with DAPI in blue) at late time points after IR (80 min, A, C). Conversely, γH2AX RIF are observed inside the heterochromatin domains at early time-points after IR (20 min, B, D). This behavior is observed at high doses (1 Gy, A, B) and low does (0.1 Gy, C, D) of X-rays. Untreated cells are also shown as a reference for the two experiments (E, F). Images were acquired using a Zeiss plan-apochromat 40X dry objective (NA of 0.95) on the AxioObserver Z1 (Carl Zeiss, Jena, 16 Germany). Images are maximum intensity projections of seven Z-stacks taken at 0.75 μm of distance from each other.

Figure 2

Model for HR repair of DSBs in euchromatin and heterochromatin. We suggest that HR repair is characterized by different dynamics in euchromatin (left) and heterochromatin (right). Euchromatin is mostly composed of single-copy sequences that can easily be repaired by HR. A) When the sister chromatid is not readily available, single copy sequences explore the nuclear volume by random walk until they find the homologous chromosome, then reduction of the movement facilitates strand invasion. B) When the sister chromatid is available, no movement is required to complete HR. Local chromatin ‘stiffness’ generated by the recruitment of silencing marks (HP1) and cohesins might facilitate initial steps of sister chromatin exchange. C) Heterochromatic repeats are potentially at risk of ectopic recombination if they remain in the heterochromatin domain, where there is a high concentration of homologous sequences present on non-homologous chromosomes. Thus, directional movement to the euchromatic domain would promote strand invasion and completion of HR using templates on sister chromatids or homologs, which would not result in detrimental translocations. Other repeated DNAs (rDNA and telomeres) feature similar directional movements during DSB repair. Steals form a time-lapse experiment with Drosophila cells show the relocalization of heterochromatic RIF (ATRIP foci that form inside the HP1a domain) to the euchromatic space [25] (scale bar = 1μm. Minutes indicate the time after IR exposure). After relocalization, cohesins would still facilitate repair by maintaining the association of the damaged DNA with the sister chromatid. Alternatively, homologous chromosomes might be used as templates for repair. In Drosophila, homologous pairing throughout interphase guarantees the proximity of homologous templates for HR repair. Notably, despite the differences between random walk in euchromatin and directional motions in heterochromatin, the mobilization of repair sites might involve similar mechanisms, including resection, checkpoint and local and global chromatin relaxation (see details in the main text).

Figure 3

RIF Dynamics in live cell imaging shows elastic and inelastic collisions. Immortalized non-malignant MCF10A human breast cells expressing 53BP1-mCherry [86] were imaged at different time points after IR (2.3 Gy). Following time-lapse, Z-stacks were collapsed to a 2D image set using maximum intensity projection, and registered to correct for nuclear motions. RIF movements are highlighted in zoomed sub-panels that illustrate various collision scenarios where RIFs merge (inelastic collision, A), split (B) or simply resolve (C). Notably, merged RIFs get larger, brighter and take longer to get resolved.

Figure 4

The number of RIF visible at each time point is an underestimate of the total number of RIF formed over time. A) Human fibrosarcoma HT1080 cells expressing 53BP1-GFP have been imaged at different time points after IR (5 cGy, [86]). B) Cartoon depicting localization of DSBs (red circles) and the corresponding RIF (green circles) inside the nucleus (blue). This cartoon matches the experiment shown in panel A. Large green arrows indicate when DSB have led to a detectable RIF. C) Quantification of RIF kinetics from panel A. Green curves in the lower part of the plot are the intensity profiles of each individual RIF as a function of time. The dotted-dash horizontal line indicates the intensity level above which RIF can be detected. Intersection of this line with intensity profiles indicates when RIF detection occurs (shown by large green arrows). The heterogeneity of repair rates can be observed, as RIF#1 is visible for much longer than RIF#2 and RIF#3. Observable RIF counts (black empty squares) and cumulative RIF counts (red full squares) can then be deduced from this detection process. Our computer model [86] provides a good prediction of both types of counts (equation 1 and dash black line for observable counts, equation 2 and solid red line for cumulated counts). Parameters k₁ and k₂ are rates for RIF induction and resolution, respectively. α is the number of naked DSB/Gy before formation of RIF, and D is the dose delivered. In contrast, Foray et al. model [89] is only able to fit the repair part of one type of count (observable RIF - dotted black line). In this model, α and β are the shape and location parameters for the Gamma probability distribution function. All data were fitted using the non-linear least squares functionality of R (http://www.r-project.org/, minpack.lm package), which uses the Levenberg–Marquardt algorithm to find a minimum solution.