A hybrid blob-slice model for accurate and efficient detection of fluorescence labeled nuclei in 3D

Abstract

BackgroundTo exploit the flood of data from advances in high throughput imaging of optically sectioned nuclei, image analysis methods need to correctly detect thousands of nuclei, ideally in real time. Variability in nuclear appearance and undersampled volumetric data make this a challenge.ResultsWe present a novel 3D nuclear identification method, which subdivides the problem, first segmenting nuclear slices within each 2D image plane, then using a shape model to assemble these slices into 3D nuclei. This hybrid 2D/3D approach allows accurate accounting for nuclear shape but exploits the clear 2D nuclear boundaries that are present in sectional slices to avoid the computational burden of fitting a complex shape model to volume data. When tested over C. elegans, Drosophila, zebrafish and mouse data, our method yielded 0 to 3.7% error, up to six times more accurate as well as being 30 times faster than published performances. We demonstrate our method's potential by reconstructing the morphogenesis of the C. elegans pharynx. This is an important and much studied developmental process that could not previously be followed at this single cell level of detail.ConclusionsBecause our approach is specialized for the characteristics of optically sectioned nuclear images, it can achieve superior accuracy in significantly less time than other approaches. Both of these characteristics are necessary for practical analysis of overwhelmingly large data sets where processing must be scalable to hundreds of thousands of cells and where the time cost of manual error correction makes it impossible to use data with high error rates. Our approach is fast, accurate, available as open source software and its learned shape model is easy to retrain. As our pharynx development example shows, these characteristics make single cell analysis relatively easy and will enable novel experimental methods utilizing complex data sets.

Laminin is required to orient epithelial polarity in theC. eleganspharynx

“…A previous study based on nuclear PPC positions described the formation of the cyst as an inflation event that separated left from right groups of nuclei (Santella et al, 2010). Indeed, in transverse imaging of the double plate, many left and right PPC nuclei appeared to move apart from each other during cyst formation (330-390 minutes, Fig.…”

“…Previous studies have shown that most embryonic cell divisions are oriented longitudinally (anterior-posterior) rather than left-right, and that cell positions in the pharyngeal cyst and at later stages are correlated with the positions of some early PPCs (Santella et al, 2010;Sulston et al, 1983). Thus, bilateral symmetry of the double plate might derive simply from the original left-right positions of the PPCs and the…”

SEGGA: a toolset for rapid automated analysis of epithelial cell polarity and dynamics

“…Although a tremendous amount of information about singlecell and collective cell behaviors can be obtained from live imaging studies, the availability of accurate and high-throughput methods for cell tracking and analysis is currently a rate-limiting step in making use of this information. Image analysis tools that detect cell nuclei can reliably track nuclear movements in C. elegans (Bao et al, 2006;Santella et al, 2010;Giurumescu et al, 2012), zebrafish (Keller et al, 2008), Drosophila (McMahon et al, 2008;Schindelin et al, 2012;Stegmaier et al, 2016) and mice (Lou et al, 2014). However, it is not possible to accurately determine cell shape and interactions from the positions of cell nuclei, as mathematical approaches that predict the outer contours of cells based on the locations of the cell centers often fail for cells that are elongated or irregular in shape, which are typical of developing epithelia Blankenship et al, 2006;Williams et al, 2014).…”

Systematic quantification of developmental phenotypes at single-cell resolution during embryogenesis

“…Automated image analysis and data mining methods are emerging to further facilitate such efforts (Dupuy et al, 2007;Long et al, 2009;White et al, 2010;Wählby et al, 2012). Early embryogenesis of C. elegans, where lineage patterning, gastrulation and extensive cell-cell signaling occur, is particularly amenable for systematic in vivo analysis because the entire cell lineage can be traced at minutelevel resolution (Schnabel et al, 1997;Hamahashi et al, 2005;Bao et al, 2006;Dzyubachyk et al, 2009;Hench et al, 2009;Santella et al, 2010;Giurumescu et al, 2012). Genome-wide RNAi has been used to analyze behaviors of individual cells up to the 4-cell stage (Sönnichsen et al, 2005).…”