A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage

Abstract

The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3D+time image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology.

An integrated modelling framework from cells to organism based on a cohort of digital embryos

“…Images of five live embryos developing from the 32-cell stage at 4–6 hours post-fertilisation (hpf) until the hatching blastula were acquired with two-photon microscopy and processed by our automated reconstruction workflow56 (Fig. 1a and Supplementary Table 1).…”

“…2d). Our visualisation interface Mov-IT56 helped validate and correct cell tracking, and manually label cells at the 32-cell stage according to their classification into four cell types with known distinct fates: mesomeres (Mes), macromeres (Mac), large micromeres (LMic) and small micromeres (SMic) (Supplementary Fig. 1b)1119.…”

“…A detailed description of the reconstruction methods, including the mathematical algorithms used, was published previously6 (Supplementary Note 1). The three main components described in the next sections are: nucleus centre detection, cell trajectory tracking, and cell membrane segmentation.…”

“…Yet, single-cell processes are inherently noisy and can lead to significant variations and heterogeneity within a priori homogeneous cell populations123. Recent advances in the quantitative live imaging of whole embryos4, including cell lineage “reconstruction”567 and gene expression “atlasing”8, mainly in the zebrafish, fruit fly, and nematode, provide an important path toward reconciling the two aspects of robustness and variability. The in toto maps at cellular resolution produced by these works allow deciphering the relationships between the single-cell features and the embryo-level dynamics underlying morphogenesis.…”

“…The structure and dynamics of the gene regulatory network (GRN) of Strongylocentrotus purpuratus have been extensively studied, leading to complete models of interactions between genes91011. Paracentrotus lividus , on the other hand, is better suited for in toto imaging at the individual-cell resolution over long periods of time due to its transparency and robustness under experimental conditions612. We deliver here the first complete methodological framework for the predictive understanding of animal embryogenesis combining in toto 3D+ time imaging, statistical and mechanical modelling.…”