Figure 1.
Graph to illustrate the differential exposure time theorem.
The graph is based on a simulation of 500 nuclei with a fixed S-phase length and cell cycle length randomly entering S-phase. The S-phases are then sorted and plotted in gray. The Y-axis has a length of 1 (all cells) and the X-axis has a length of one cell cycle (TC). The slope of the line formed by the end points of the S-phases is therefore by definition 1/TC. Thymidine analogues are incorporated into the nucleus during the S-phase (between the black lines). The fraction of labelled nuclei is thus determined by the length of the S-phase plus the time of exposure to the thymidine analogue divided by the total length of the cell cycle [7]. When two different exposure times are applied, either by two different thymidine analogues or in two different animals, the difference in fraction of labelled nuclei (ΔF) is linearly related to the difference in exposure time (ΔT) (red triangle). Because the slope of this relation is equal to 1/TC, the cell cycle length can be calculated (red box). Similarly, the length of the S-phase can be determined from the slope in the blue triangle and the calculated TC (blue box).
Figure 2.
Cross-reactivity and validation of antibody staining.
Section of an embryo exposed to IdU shows specific staining using an antibody against IdU (Panel A). When an antibody against CldU is used there is no aspecific staining visible (Panel C). When an embryo is exposed to CldU and an antibody agains IdU is used some cross reactivity is observed (Panel B). Panel D shows specific staining for CldU. Abbreviations: ift: Inflow Tract; nt: Neural Tubel; oft: Outflow Tract; v: Ventricle. Panel E shows the relation between the number of nuclei labelled for IdU and for CldU at equal exposure times. Each point represents a section. There was no significant difference between 2 and 4 hours of exposure time. The linear relation shows a high correlation coefficient (R2 = 0.991) and detection of 7.2% less IdU than CldU positive nuclei.
Figure 3.
Image analysis and visualisation.
Panel A. Using a Sytox green staining, all nuclei are first detected based on a local-maxima threshold. All detected objects that were at least twice as large as the median object size were processed to separate these fused nuclei (inserts). Panel B shows a schematic overview of the image processing steps involved in the recognition of IdU- and CldU-positive nuclei. After the detection of the Sytox green stained nuclei, each nucleus is individually processed. A zone is selected around all nuclei which will be excluded in the following measurement (gray zone). For each nucleus within the region of interest (myocardium), the algorithm measures the signal in (red area) and around (green area) the nucleus in the IdU and CldU channels. The measurement of the local background excludes the locations at which other nuclei were detected (gray zone). When the signal in the nucleus is at least a standard deviation above the background, the nucleus is classified as positively labelled. The program generates control images both for the nuclei detection as well as for which nuclei are positive for the proliferation markers. The difference between the two proliferation markers is used to determine ΔF (number of green nuclei divided by total number of nuclei). Panel C shows how the quantitative information can be projected onto a reconstruction or onto the original section. Each unit in the boxel representation has a volume of approximately 213 µm3, and is the central boxel of the sampling volume of approximately 1053 µm3 that is required for reliable measurement of the labelling indices [15].
Figure 4.
Application in heart development.
3D visualisation of cell cycle length in the heart at stages HH9 (Panel A), HH12 (Panel B) and HH16 (Panel C) of chicken embryonic development. The pointer in panel B indicates the region with a high proliferation rate at the site of early ventricle formation. Panel C shows the quantitative reconstructions of the individual labelling indices for CldU and IdU, on which the cycle lengths are based. The pointers in the CldU reconstruction indicate areas in which a low fraction of cells is positive in both CldU and IdU reconstructions, resulting in a low labelling difference and thus a long cell cycle length. The pointers in the IdU reconstruction show large differences in IdU and CldU labelling indices, indicating short cell cycle lengths. Note the heterogeneity in cell cycle lengths in different parts of the heart at every stage. Interactive versions of the 3D-reconstructions can be found in Interactive 3D-pdf S1.
Figure 5.
Cell size - cell cycle length clustering and visualisation.
Panel A shows a k-means cluster analysis of boxels based on their cell volume and their cell cycle length. Panel B shows the result of plotting cluster membership of each boxel into the HH12 myocardium reconstruction. Although spatial information was not used in the cluster procedure, the resulting clusters show clear spatial continuity.