Highlights d Btd/Eve-dependent lateral MyoII shortens cells to initiate CF d Single-cell row Btd/Eve positional code accounts for only 80% of CF-initiating cells d Mis-specification arises due to MyoII noise, and yet the cells align among themselves d Mechanical coupling via planar polarized MyoII aligns cells to ensure CF linearity

Activation is an essential process that accompanies fertilisation in all animals and heralds major cellular changes, most notably, resumption of the cell cycle. While activation involves wave-like oscillations in intracellular Ca2+ concentration in mammals, ascidians and polychaete worms and a single Ca2+ peak in fish and frogs, in insects, such as Drosophila, to date, it has not been shown what changes in intracellular Ca2+ levels occur. Here, we utilise ratiometric imaging of Ca2+ indicator dyes and genetically encoded Ca2+ indicator proteins to identify and characterise a single, rapid, transient wave of Ca2+ in the Drosophila egg at activation. Using genetic tools, physical manipulation and pharmacological treatments we demonstrate that the propagation of the Ca2+ wave requires an intact actin cytoskeleton and an increase in intracellular Ca2+ can be uncoupled from egg swelling, but not from progression of the cell cycle. We further show that mechanical pressure alone is not sufficient to initiate a Ca2+ wave. We also find that processing bodies, sites of mRNA decay and translational regulation, become dispersed following the Ca2+ transient. Based on this data we propose the following model for egg activation in Drosophila: exposure to lateral oviduct fluid initiates an increase in intracellular Ca2+ at the egg posterior via osmotic swelling, possibly through mechano-sensitive Ca2+ channels; a single Ca2+ wave then propagates in an actin dependent manner; this Ca2+ wave co-ordinates key developmental events including resumption of the cell cycle and initiation of translation of mRNAs such as bicoid.

Cell function is regulated by the spatiotemporal organization of the signaling machinery, and a key facet of this is molecular clustering. Here, we present a protocol for the analysis of clustering in data generated by 2D single-molecule localization microscopy (SMLM)-for example, photoactivated localization microscopy (PALM) or stochastic optical reconstruction microscopy (STORM). Three features of such data can cause standard cluster analysis approaches to be ineffective: (i) the data take the form of a list of points rather than a pixel array; (ii) there is a non-negligible unclustered background density of points that must be accounted for; and (iii) each localization has an associated uncertainty in regard to its position. These issues are overcome using a Bayesian, model-based approach. Many possible cluster configurations are proposed and scored against a generative model, which assumes Gaussian clusters overlaid on a completely spatially random (CSR) background, before every point is scrambled by its localization precision. We present the process of generating simulated and experimental data that are suitable to our algorithm, the analysis itself, and the extraction and interpretation of key cluster descriptors such as the number of clusters, cluster radii and the number of localizations per cluster. Variations in these descriptors can be interpreted as arising from changes in the organization of the cellular nanoarchitecture. The protocol requires no specific programming ability, and the processing time for one data set, typically containing 30 regions of interest, is ∼18 h; user input takes ∼1 h.

No abstract