Automated Characterization of Amoeboid Motility
Traditionally, amoeboid motility has been characterized by a number of different parameters. Some, such as velocity, directional persistence, and chemotactic index, are determined by the position of the cell’s centroid as it migrates in response to external chemical cues, a process known as chemotaxis. Characterizations which address cellular morphology are based on cell shape parameters such as perimeter, area, roundness, and body orientation. Though these parameters can be used to identify some differences between strains of chemotactic cells, they primarily provide global information about chemotaxis and chemoattractant-induced cell shape changes, hence are insufficient to distinguish cell strains based on local morphological information, such as pseudopodial protrusions, that typify amoeboid motility. Even when the activities of pseudopodia are described in some studies, the protrusions have been identified and outlined manually. In addition to being highly time consuming, these manual methods have the drawback that they are based on subjective judgements. Thus, an efficient and systematic approach is necessary for cell shape characterization.
We develop a series of automated methods to characterize amoeboid locomotion based on the skeleton of a planar shape. Skeletonization, also known as the medial axis transform, is a technique in morphological image processing used to reduce a binary shape into a series of connected lines — the skeleton — which roughly maintain the form of the shape. Our methods are capable of capturing the stochastic features of pseudopodial protrusions and retractions for various phenotypes. Moreover, our methods are able to describe the temporal dynamics of individual pseudopodia by obtaining the time series of protrusion and retraction angles, and modeling it using a second-order autoregressive process. Furthermore, our results can be coupled with the measurements of different cellular component distributions along the cell body, thus facilitate the understanding of the relation between cellular polarization and motility.
The figure above shows five snapshots at different time points from a chemotaxing cell moving towards a needle. They show the cell outline (white), the skeleton (green) and the tips (protrusions in red, retractions in blue) in each image. The times (in seconds) when each image was taken from the beginning of the movie are labeled at the lower-left corners. The scale bar at the lower-right corner in the last image represents the length of 5 µm.
Traditionally, amoeboid motility has been characterized by a number of different parameters. Some, such as velocity, directional persistence, and chemotactic index, are determined by the position of the cell’s centroid as it migrates in response to external chemical cues, a process known as chemotaxis. Characterizations which address cellular morphology are based on cell shape parameters such as perimeter, area, roundness, and body orientation. Though these parameters can be used to identify some differences between strains of chemotactic cells, they primarily provide global information about chemotaxis and chemoattractant-induced cell shape changes, hence are insufficient to distinguish cell strains based on local morphological information, such as pseudopodial protrusions, that typify amoeboid motility. Even when the activities of pseudopodia are described in some studies, the protrusions have been identified and outlined manually. In addition to being highly time consuming, these manual methods have the drawback that they are based on subjective judgements. Thus, an efficient and systematic approach is necessary for cell shape characterization.
We develop a series of automated methods to characterize amoeboid locomotion based on the skeleton of a planar shape. Skeletonization, also known as the medial axis transform, is a technique in morphological image processing used to reduce a binary shape into a series of connected lines — the skeleton — which roughly maintain the form of the shape. Our methods are capable of capturing the stochastic features of pseudopodial protrusions and retractions for various phenotypes. Moreover, our methods are able to describe the temporal dynamics of individual pseudopodia by obtaining the time series of protrusion and retraction angles, and modeling it using a second-order autoregressive process. Furthermore, our results can be coupled with the measurements of different cellular component distributions along the cell body, thus facilitate the understanding of the relation between cellular polarization and motility.
The figure above shows five snapshots at different time points from a chemotaxing cell moving towards a needle. They show the cell outline (white), the skeleton (green) and the tips (protrusions in red, retractions in blue) in each image. The times (in seconds) when each image was taken from the beginning of the movie are labeled at the lower-left corners. The scale bar at the lower-right corner in the last image represents the length of 5 µm.
Publications
- Chen, L., M. Iijima, M. Tang, M.A. Landree, Y.E. Huang, Y. Xiong, P.A. Iglesias and P.N. Devreotes. “PLA2 and PI3K/PTEN pathways act in parallel to mediate chemotaxis.” Developmental Cell 12:603–614, Apr. 2007.
- Kabacoff, C., Y. Xiong, R. Musib, E.M. Reichl, J. Kim, P.A. Iglesias and D.N. Robinson. “Dynacortin facilitates polarization of chemotaxing cells.” BMC Biology 5:53, Nov. 26, 2007.
- Kamimura, Y., Y. Xiong, P.A. Iglesias, O. Hoeller and P.N. Devreotes. “PIP(3)-independent activation of TorC2 and PKB at the cell's leading edge mediates chemotaxis.” Current Biology 18(14):1034-1043, July 22, 2008.
- Tang, L., Franca-Koh, J., Xiong, Y., Chen, M-Y., Long, Y., Bickford, R.M., Knecht, D.A., Iglesias, P.A., and Devreotes, P.N.
“Tsunami, the Dictyostelium homolog of the Fused kinase is required for polarization and chemotaxis.”
Genes & Development 22:2278-2290, 2008.