A semi-local neighborhood-based framework for probabilistic cell lineage tracing

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.

The Regulatory Landscape of Lineage Differentiation in a Metazoan Embryo

“…We found that 41% of the time the phenotypes were penetrant at the cellular level (Figure 1H). To ensure correct of lineage tracing, we performed multiple rounds of manual curation on the automatically generated lineages (Santella et al, 2014) (Figures S2D and Extended Experimental Procedures). Based on human examination of 100 randomly picked cell tracks post curation, we found that 96% of terminal cells were correctly traced (Figure 1I).…”

“…3D, time-lapse imaging now allows in toto imaging of metazoan embryogenesis in different model organisms and tracking of individual cells (Bao et al, 2006; Keller et al, 2008; McMahon et al, 2008; Udan et al, 2014; Wu et al, 2013; Xiong et al, 2013). In C. elegans , it allows direct tracing of the whole cell lineage (Bao et al, 2006; Santella et al, 2014; Santella et al, 2010). By combining automated lineaging with tissue-maker expression-based assessment of cell types, we have recently shown that progenitor cell fates can be systematically assayed (Du et al, 2014).…”

Combinatorial decoding of the invariant C. elegans embryonic lineage in space and time

“…These efforts generated an integrated suite of methods and tools that dramatically increased efficiency in lineage tracing and allowed new applications. After collecting 4D fluorescent images using a wide variety of microscopy platforms (Bao et al ., ; Moore et al ., ; Murray and Bao, ; Richards et al ., ; Wu et al ., ), the analysis software StarryNite identifies (Santella et al ., ), and tracks (Santella et al ., ) nuclei over time. The automated process is highly accurate (>99.6%) but the sheer number of cells being identified and tracked requires manual curation and editing of the automated output, which is facilitated by custom software (AceTree)(Boyle et al ., ).…”

Infrared laser-induced gene expression for tracking development and function of single C. elegans embryonic neurons

“…Indeed, recent improvements in computer algorithms now allow real-time nuclear tracking in C. elegans embryos5051. Thus a complete description of C. elegans nervous system assembly on a cell-by-cell basis should be feasible.…”