We built a digital nuclear atlas of the newly hatched, first larval stage (l1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. the atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a threedimensional image of an l1 worm. We achieved 86% accuracy in identifying the 357 nuclei automatically. this computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen. Despite the detailed knowledge of the anatomy of the nematode C. elegans 1 as well as its determined cell lineage 2,3 , the mapped connectivity of its nervous system 4,5 and its sequenced genome 6,7 , we still lack a three-dimensional (3D) digital atlas of positions of nuclei in any postembryonic stage. Such an atlas has several potential applications. First, it provides us with previously unavailable quantitative knowledge about the degree of stereotypy of the positions of nuclei and the specific spatial relationships between different cells. Second, the atlas can serve as a standard template; we can compare any 3D image of a wild-type C. elegans to the atlas and extract the identities of individual nuclei using an automated approach. This is essential for high-throughput analysis of cellular information such as gene expression at single-cell resolution. Such an analysis provides much richer information than does analysis of expression data from a DNA microarray experiment 8,9 as DNA microarrays reveal average expression from tissue or from the entire individual but not the expression in an individual cell. Prior to this study, the anatomy of C. elegans has been described qualitatively by images with a text description or two-dimensional sketches 10 . Early efforts using electron microscopy analyses have resulted in detailed views of the anatomy 10 and even a connectivity graph of the nervous system 4,5 , but to date, manual or automated segmentation of the fine structure of such an ultrahigh-resolution image stack has not been demonstrated. Whereas one might contemplate carrying out such a manual segmentation for a single worm, doing so for enough worms to deliver statistical information on the location of nuclei is effectively impractical. Our method for automatically analyzing individual cells in postembryonic worms complements the similar capability developed previously for the embryo 11,12 . However, the computational problem is completely different. The previous method consists of tracking nuclei as they divide in vivo using known cell lineage information. In this work, we identified nuclei in situ without the help of temporal or lineage information. Moreover, our method is general and could be applied to other stereotypic systems, such as later post-embryonic worm stages or the fruit fly embryonic nervous system 13 . Here we present the method we used to build the atlas, followed by analyses of the model to confirm that it is well-constructed and recapitulates known biology. Then we describe our automated approach for using the atlas to annotate cell identities in images of first larval stage (L1) worms and demonstrate its accuracy. results We used DAPI (4,6-diamidino-2-phenylindole) to stain the nuclei of all 558 cells. We used a myo-3:GFP transgene to label the nuclei of the 81 body wall muscle cells and 1 depressor muscle cell. These nuclei were fiducial markers, used by our manual and automated approach to annotate cells. We used a gene encoding monomeric Cherry protein (mCherry) driven by a promoter from a gene of interest to reveal expression in a set of target cells. We collected 3D images of C. elegans at the L1 stage using a Leica confocal microscope (Fig. 1a) with a ×63 oil lens and x-y and z dimension sampling set at 0.116 µm and 0.122 µm per pixel, respectively. To build a standard digital atlas, we first computationally straightened the curved worm body in the 3D image into a rod shape 14 (Fig. 1b, Supplementary Fig. 1 and Supplementary  Video 1) . The method first detects the principal curve or 'backbone' that represents the anterior-posterior line that passes from head to tail through the center of a straightened worm (Supplementary Fig. 1b) . It then generates one-pixel separated planes orthogonal to the backbone and restacks them along a straight anterior-posterior line, making the planes parallel to each
Based on this work, Long et al. REF have constructed a 3D map for the first larval stage of C. elegans (L1).
A 3D digital atlas of C. elegans and its application to single-cell analyses
Nature Methods
Nature Methods
Medicine Biology