Abstract
BackgroundAdvances in fluorescence labeling and imaging have made it possible to acquire in vivo records of complex biological processes. Analysis has lagged behind acquisition in part because of the difficulty and computational expense of accurate cell tracking. In vivo analysis requires, at minimum, tracking hundreds of cells over hundreds of time points in complex three dimensional environments. We address this challenge with a computational framework capable of efficiently and accurately tracing entire cell lineages.ResultsThe bulk of the tracking problem—tracking cells during interphase—is straightforward and can be executed with simple and fast methods. Difficult cases originate from detection errors and relatively rare large motions. Therefore, our method focuses computational effort on difficult cases identified by local increases in cell number. We force these cases into tentative cell track bifurcations, which define natural semi-local neighborhoods that permit Bayesian judgment about the underlying cell behavior. The bifurcation judgment process not only correctly tracks through cell divisions and large movements, but also offers corrections to detection errors. We demonstrate that this method enables large scale analysis of Caenorhabditis elegans development, an ideal validation platform because of an invariant cell lineage.ConclusionThe high accuracy achieved by our method suggests that a bifurcation-based semi-local neighborhood provides sufficient information to recognize dependencies between nearby tracking choices, and to interpret difficult tracking cases without reverting to global optimization. Our method makes large amounts of lineage data accessible and opens the door to new types of statistical analysis of complex in vivo processes.
Highlights
Advances in fluorescence labeling and imaging have made it possible to acquire in vivo records of complex biological processes at unxcbuprecedented spatial and temporal resolution
Performance of the tracking algorithm was evaluated on C. elegans embryos imaged from the 4-cell to 350-cell stage, which covers ~4 hours of embryogenesis with ~200 time points at 75 second intervals, totaling approximately 25,000 nuclear objects to be tracked per embryo
In terms of cumulative track accuracy ~60% of the cells in the last frame are correctly tracked from the beginning through ~200 time points and 6 rounds of cell divisions with no errors intervening along the way (Figure 3a)
Summary
Advances in fluorescence labeling and imaging have made it possible to acquire in vivo records of complex biological processes. At minimum, tracking hundreds of cells over hundreds of time points in complex three dimensional environments. We address this challenge with a computational framework capable of efficiently and accurately tracing entire cell lineages. Advances in fluorescence labeling and imaging have made it possible to acquire in vivo records of complex biological processes at unxcbuprecedented spatial and temporal resolution. The true value of in toto imaging lies in the possibility of tracing the entire cell lineage that underlies development. Accuracy is difficult to attain because cells are densely packed, and this is exacerbated by limited optical resolution due to sample properties and the need to minimize photobleaching and phototoxicity
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