Page 61 - Haematologica April 2020

Megakaryocytes modulate BM cell mobilization
emphasize the need for (customized) multistage segmen- tation pipelines with active artifact removal when study- ing complex specimens. While both common pipelines failed significantly, the two-pass algorithm performed closest to our custom pipeline, albeit with some flaws. Besides the risk of over-segmentation, further manual assessment confirmed incomplete segmentation of larger megakaryocyte somata with weak and irregular staining as often found in typical samples. Unfortunately, this results in invaginations and consequently volume under- estimation. During segmentation, seeding points were often not set properly. They were preferentially placed on high intensity membrane or cell-cell touching areas and often missed cell centers, which leads to inaccurate deter- mination of cell volumes, but similar cell numbers (Figure 2D, Online Supplementary Figure S2D).
Previous studies often utilized Ilastik pixel classification for discrimination of distinct objects such as co-cultured cells.40 In line with recent work,25 we demonstrated suc- cessful segmentation of challenging tissue structures. Although the best results were achieved here with the full feature set for pixel classification, these sets could be reduced and optimized to smaller structure/pattern sizes that also suit memory-limited scenarios.
The segmented objects of the LSFM images are not only important for proper quantitative imaging, but are also very advantageous when it comes to realistic simulations of cellular distributions, dynamics and interactions of cells within the BM. Thus, we found that real sample templates were highly advantageous, in terms of accuracy, com- pared to simplified artificial 3D objects. Of course, the conventional method using periodic and other simple structures would minimize computational time, but could lead to biased results, masking important features of a given distribution.
Previous studies have shown that the deletion of megakaryocytes activates quiescent HSC and expands the HSC pool as well as increasing HSC mobilization and proliferation.16-18 These effects could be partially repro- duced by ablation of cytokines, such as TGFβ117 and CXCL416 in megakaryocytes and platelets. However, as megakaryocytes, despite their relatively low number (accounting for less than 0.1% of all BM cells), make up a significant volume within the BM and are distributed along the blood vessels, we hypothesized that megakary- ocytes might serve as passive obstacles hindering the egress of other cells from the BM. As the biomechanical barrier function of megakaryocytes cannot be technically uncoupled from the potential chemical effects (e.g. cytokine release) of megakaryocytes, which are also abol- ished if these cells are depleted, in vivo, we took advan-
tage of mathematical modeling approaches using LSFM- derived objects. These simulations based on 3D Brownian dynamics clearly demonstrate that megakary- ocytes might act as a biomechanical restraint hindering BM egress of HSC or neutrophils (Figure 4). Importantly, this effect comes into play even under circumstances such as chemotactic cues or high cell velocities, indicating that it is an important factor modulating the egress of cells from the BM. Other cell features, such as deformability have also been shown to be important when it comes to extravasation and tumor growth41 or immune responses.42 Extravasation conditions and prerequisites have been modeled previously e.g. by Xiao and colleagues43 with the interesting result that cell shape rather than elasticity may play an important role when squeezing through a narrow gap. This knowledge may guide more complex simula- tions in the future. However, to date it exceeds the com- putational power of common laboratories and facilities. In contrast, the simulations presented here can be run on a single workstation in a few hours, still being sufficient to describe a typical large-tissue scenario observed in ani- mal experiments. One limitation of using platelet deple- tion is that this treatment might potentially affect other features of the BM environment that could influence the migration of BM cells. On the other hand, the use of anti- GPIbα antibodies to deplete platelets is the ‘gold stan- dard’ in the field and has no obvious effects on immune cells.35 Moreover, our first in vivo data on neutrophil mobility in naïve and platelet-depleted mice (Figure 5; Online Supplementary Tables S3 and S4) support the hypotheses derived from our mathematical modeling approach, as the saturation limit of the neutrophil MSD trajectories in platelet depletion was significantly reduced compared to steady-state conditions (Figure 5G; Online Supplementary Table S3). Consequently, this study points to the importance of biomechanical properties of the BM environment in regulating cell motility, a factor which has so far not been appreciated sufficiently. Moreover, our study showcases how the combination of advanced imaging approaches in combination with computational simulations can refine hypotheses.
Funding
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 374031971 – TRR 240, TP B06, and the Rudolf Virchow Center of the University of Würzburg, Germany.
Acknowledgments
The authors thank Hannah Heil (RVZ, University of Würzburg) for help with the graphics concerning Figure 4.
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