The nuclear architecture and its cancer-related changes have been studied since Boveri first postulated that the nuclear architecture differs between normal and cancer cells [Boveri, 1914, 2008]. Over the course of the last century the structure of DNA has been unraveled at various length scales. The structure by itself does not, however, reveal its spatial organization within the nucleus. Many current models about the nuclear architecture are studied in animals and human cell lines. For clinical applications such models also need to be validated in primary human tumor cells.
The existence of individual chromosomes in dividing nuclei was first observed in mitotic cells [Flemming, 1882]. Chromosomes occupy distinct regions in the interphase nucleus, designated as chromosome territories (CTs) [Cremer and Cremer, 2006a,b]. The position of each human CT inside the nucleus is determined by its size and gene density [Tanabe et al., 2002]. As the spatial distribution of DNA is non-random, it is important to assess the spatial DNA structure. This would include measurements at length scales larger than the typical sizes of the quaternary nucleic acid structure.
Microscopic analyses of the DNA structure in cell nuclei have been performed since the wide-scale availability of digital image processing. Automatic estimation of the number of low- and high-density DNA regions within a white blood cell has been performed since the 1980s [Bins et al., 1981]. Several additional features, including the granularity of the spatial DNA distribution, were also measured during that time [Young et al., 1986]. It has been noted that chromatin is structurally organized on various length scales that can be made visible using light microscopy [Einstein et al., 1998]. Differences in the microscopic DNA structure have been described using various names, including chromatin condensation, chromatin structure, and chromosome packaging, in a variety of diseases, including cancer [Hannen et al., 1998; Vergani et al., 1999; Natarajan et al., 2012].
3D structured illumination microscopy (SIM) is a superresolution imaging modality that has only recently found its way to the biology laboratory. This methodology offers a higher image resolution than conventional epifluorescence widefield microscopy through the use of heterodyne detection of a fluorescent sample illuminated by a periodic pattern [Heintzmann and Cremer, 1999; Cragg and So, 2000; Frohn et al., 2000; Gustafsson, 2000]. It has been shown that 3D-SIM images of DNA, stained with DAPI, reveals structural information that had not been seen with conventional microscopy methods [Schermelleh et al., 2008]. Investigation of the nuclear architecture using fluorescent in situ hybridization (FISH) showed that, during FISH experiments, key characteristics of the ultrastructure are preserved [Markaki et al., 2012]. This suggests that the nuclear architecture, as observed by 3D-SIM, remains stable for different sample preparation techniques.
The DNA structure inside the interphase nucleus can be visualized with 3D-SIM at microscopic length scales. Visual inspection of 3D-SIM images of different cell types shows qualitative differences in the DNA structure between cell types. In order to measure these differences objectively, a method to explore and quantify the structure is needed. In particular, the granularity of the DAPI-stained DNA structure can then be assessed using 3D-SIM.
We choose to study the DNA structure in Hodgkin’s lymphoma (HL) cells, because of the unique nature of this form of lymphoid cancer. Malignant cells in HL are mononucleated Hodgkin cells (H) and bi- or multinucleated Reed–Sternberg cells (RS). The RS cell is the diagnostic cell for this malignancy. A variety of cellular functions are affected in these cells in comparison to the normal B lymphocytes from which they originate [Kuppers et al., 2012]. A multitude of translocations have been identified in RS cells [MacLeod et al., 2000] and their nuclear architecture becomes progressively more disorganized as the number of subnuclei increases [Knecht et al., 2009; Guffei et al., 2010]. This includes an increase in the number of centrosomes and aberrant multi-polar mitotic spindles [Martin-Subero et al., 2003; Knecht et al., 2009]. The nuclear architecture of and the difference between H and RS cells has also been linked to the clinical outcome of the disease [Knecht et al., 2012].
In this article, we first aimed to quantitatively describe the size distribution and assess the differences of the DNA structure and the DNA-free space(s) in lymphocytes, H cells, and RS cells. When we refer to DNA size in this paper, we refer to the physical “cluster” sizes visible in the 3D-SIM images, rather than the number of base pairs of these DNA clusters. When we refer to density, we discuss the relative local intensity in images and not the absolute concentration of DNA. Second, we have investigated the spatial relation between the nucleolus-related protein UBF and the DNA-free space, which is part of the complement (or negative) of the DNA structure. We have found a significant and progressive difference in DNA structure and DNA-free space between normal, Hodgkin, and Reed–Sternberg cells.
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- MATERIALS AND METHODS
- Supporting Information
We have described, to the best of our knowledge for the first time, the intranuclear DNA structure of normal and cancer cells using a superresolution microscopy method. We have been able to quantify the DNA structure revealed by high resolution light microscopy successfully. In particular, we have been able to measure structures at the 200–700 nm size range. We have observed that many more of these sub-micron structures are present and that they are smaller in size in HL cells than in control lymphocytes. When we measured the properties of the SIM DAPI intensity histograms, we noted an increased skewness for the HL cells. This means that these malignant cells have a more asymmetric DNA distribution than lymphocytes. This can be attributed to the apparent higher degree of clustering in these cells. The RS cells have a larger spread in pixel intensities than H cells, as evidenced by their increased c.o.v. This means that the DNA density in these multinucleated cells is more varied than for the mononucleated H cells.
These structures might appear due to changes in the condensation of the DNA. As H and RS cells are larger, the DNA might also be spread out over a larger volume. If the spreading is uneven, this could lead to local “patches” of DNA. It might also be linked to a difference in chromatin organization, possibly measured with chromosome conformation capture techniques [Nagano et al., 2013], between these cells and healthy lymphocytes. We have previously shown that, in the HD cell-line U-HO1-PTPN1, PTPN1 induced down-regulation of STAT5A was associated with multi-nuclearity and high apoptotic index compared to the U-HO1 cell-line [Knecht et al., 2010]. The DNA content varies between different subnuclei in RS cells, some subnuclei are more DNA-rich than others [Guffei et al., 2010].
We measured the DNA-free space in these cells as well. We observed an increase in the DNA-free space in HL compared to lymphocytes, as well as the formation of “holes” in the nucleus. To check whether the DNA-free space or the holes represented nucleoli, we stained for UBF. We found during HL progression from H cells to RS cells with increased multinuclearity, that both the portion of DNA-free space filled with UBF and the rate of visible holes filled with UBF decreased significantly. Nucleoli can be disrupted in cancer [Boulon et al., 2010], which would explain why the UBF signal is not confined to one nucleolus per subnucleus in the malignant cells. The reduction of relative UBF content in the DNA-free space for H and RS cells poses the question whether something else takes its place. This space might now be filled by other nucleolar proteins, different nuclear bodies [Fong et al., 2013], transcription factories or could simply be devoid of stable sub-nuclear organelles.
We do not claim that this is the only microscope modality that could visualize these structures. Other superresolution methods, or microscopes that perform optical sectioning, could lead to similar images as in Figures 1 and S1. Such images should then lead to similar granulometry results. The structures with frequency content that is within the pass-band of the objective lens might be recovered from widefield microscopy images using post-processing methods.
Previous studies measuring aspects of the nuclear architecture within Hodgkin and Reed–Sternberg cells have detected a progressive disruption of the nuclear organization [Martin-Subero et al., 2003; Knecht et al., 2009; Guffei et al., 2010]. Our measurements quantitatively revealed the progressive disruption of nuclear DNA organization in HL. We have, for the first time, shown a progressive trend in the organization of DNA using superresolution microscopy. This trend starts at the control lymphocytes, moves towards Hodgkin cells, and then progresses to Reed–Sternberg cells. Within the population of Reed–Sternberg cells we found the same trend with increasing multinuclearity.
We have performed our study on an HL cell line. The measurements described in this article can be extended in two ways. First, it would be desirable to perform the same measurements in primary tumor cells of clinical HL samples. Care should be taken in choosing an embedding medium with proper refractive index. As we currently perform the measurements in 2D slices, it should be possible to do this in tissue, in particular lymph node biopsies. Second, it should be possible to investigate other cancers to determine whether our observations are specific for HL or whether they would apply more generally to other cancers as well. If these changes to the nucleus are common to cancer cell nuclei, then the question arises if the same changes would be detected for different cancers or whether they would be cancer specific. The initial candidates for similar studies should be other hematological malignancies.
The features of the nuclear architecture we measure follow a progressive trend with progressive cell conditions in HL. More aggressive cases of HL can, in some cases, be identified based on the nuclear organization of the H and RS cells in those tumors [Knecht et al., 2012]. The nuclear DNA structure might, therefore, also be related to the aggressiveness of HL. Whether the measures presented here are correlated with clinical outcome, could be investigated by comparing HL cases of patients who respond to treatment versus those who recur.
The measures of the DNA structure and DNA-free space were performed over the entire nucleus. There might be a difference in these features between chromosomes, for instance the length, gene density, activity, and/or radial position of each chromosome might play a role in the DNA organization. To test this, CTs would need to be stained individually. It should then be possible to check whether there are differences between the DNA organization between CT’s, or for the same CT between a healthy and disease state. It might also be possible to determine the location of the DNA-free space in relation to the interface between CT’s. This could ultimately determine which boundary model—either the interchromatin domain model or the interchromosomal network [Branco and Pombo, 2006]—is correct; it could lead also to a different model altogether.
Cancer is a disease of DNA organization [Pienta et al., 1989] and for the first time we can address the changes in the organization in detail. We have shown a difference for both the DNA structure and DNA-free space in the nucleus and found both nuclear and nucleolar remodeling. This study can be seen as the tip of an iceberg, where we have measured a selected set of structural changes in one cell line. There are a wide variety of other features and other systems in which this can be studied. This is, however, the first superresolution view of these nuclear alterations. The DNA architecture in cancer might be a hallmark of the underlying genomic instability and cellular reprogramming that promotes cell proliferation, evasion from apoptosis and immunosurveilance.