Spatiotemporal AQ 1 Cytometry — Simultaneous Analysis of DNA Replication and Damage

MANY subcellular phenomena occur in discrete spatial regions of the nucleus or cytoaplasm. Nuclear processes like DNA replication, transcription, or splicing take place in such small regions defined as foci or microfoci. Using the methods of modern optical microscopy these processes can be visualized in 3D space and time. Numerous labeling techniques are available for visualization of various cellular components and processes that occur in these structures. As new microscopy methods are being developed, resolution of images improves and currently several approaches make it possible to record images with resolution exceeding the Abbe limit. An ability to image subcellular microfoci in 3D space, and often also in time, using techniques of tagging with fluorescent proteins that report time-related events opens new avenues of investigation of cellular processes. The article by Berna s et al. (1) provides a novel protocol allowing correct spatiotemporal observation of events in close proximity, as well as the ability to judge their association. DNA damage response (DDR) is the primary guardian of our genetic stability, good health, and longevity. It is a set of events initiated by insults causing loss of DNA-integrity that ultimately leads (when possible) to full restoration of the damaged DNA fragment. DDR is initiated primarily by the post-translational modification of several proteins which are directly or indirectly playing important roles in different signaling pathways, not only DNA repair, but also cell cycle progression, cell death, and cell senescence (2). While the primary response is mostly of protein modification type (mainly phosphorylations and poly-ADP-ribosylations), modulation of transcription and translation also occurs, especially in later phases of the response (3). When two nuclear processes such as DNA damage and replication are causally related, the microfoci corresponding to these events are expected to overlap. The causal relationship may be strong or weak, i.e. there may be a one-to-one relationship between both types of foci, or—more often—just a weak tendency or a preference, which depends on various modifying conditions. How should one measure the strengths, likelihood, or temporal dependence of such causal relationships? There is a need to put metrics on spatial relationships between foci representing the phenomena of both classes. This means, in practice, measuring the number of foci that are overlapping, closely spaced, and located far from each other, in each cell, and repeating this process in many cells. The report by Berna s et al. (1) describes a combined cytoametric approach to this problem. It employs image analysis of confocal images, and combines these data with information derived from laser scanning cytoametry. In most instances, cancer cells proliferate with much higher frequency as compared to their surrounding tissues. This feature of cancer cells is explored, among others, by a set of drugs called topoisomerase inhibitors (i.e., camptothecin, etoposide). Those drugs freeze the action of topoisomerases (the DNA-unwinding enzymes) causing formation of a “cleavable complex,” thus leading to the generation of double stranded breaks in proliferating cells (2,4). Thus, especially when topoisomerase-inhibitors are used, the two nuclear processes, DNA replication and DNA-damage, are spatially, temporary, and casually related to each other, while taking place in small regions (foci or microfoci). Depending on the insult causing DNA-damage, the relationship (the distance) between them could be either strong or weak. This highly depends from the type of conditions that cause—or favor— DNA damage, like the type of physical (UV, X-rays, gammairradiation), chemical insults (various carcinogens), or natural propensities of DNA at certain regions (5,6). In the article by Berna s et al. (1), the authors have measured a number of foci that are overlapping, closely spaced, and located far from each other in a cell. Theoretically, counting the distance between foci looks easy. But in reality, it is complicated because of its structural dissimilarity. We could even find from their results that foci do not represent perfect