Stochastic De-repression of Rhodopsins in Single Photoreceptors of the Fly Retina

The photoreceptors of the Drosophila compound eye are a classical model for studying cell fate specification. Photoreceptors (PRs) are organized in bundles of eight cells with two major types – inner PRs involved in color vision and outer PRs involved in motion detection. In wild type flies, most PRs express a single type of Rhodopsin (Rh): inner PRs express either Rh3, Rh4, Rh5 or Rh6 and outer PRs express Rh1. In outer PRs, the K50 homeodomain protein Dve is a key repressor that acts to ensure exclusive Rh expression. Loss of Dve results in de-repression of Rhodopsins in outer PRs, and leads to a wide distribution of expression levels. To quantify these effects, we introduce an automated image analysis method to measure Rhodopsin levels at the single cell level in 3D confocal stacks. Our sensitive methodology reveals cell-specific differences in Rhodopsin distributions among the outer PRs, observed over a developmental time course. We show that Rhodopsin distributions are consistent with a two-state model of gene expression, in which cells can be in either high or basal states of Rhodopsin production. Our model identifies a significant role of post-transcriptional regulation in establishing the two distinct states. The timescale for interconversion between basal and high states is shown to be on the order of days. Our results indicate that even in the absence of Dve, the Rhodopsin regulatory network can maintain highly stable states. We propose that the role of Dve in outer PRs is to buffer against rare fluctuations in this network

The nuclear transport factor CSE1 drives macronuclear volume increase and macronuclear node coalescence in Stentor coeruleus.

Stentor coeruleus provides a unique opportunity to study how cells regulate nuclear shape because its macronucleus undergoes a rapid, dramatic, and developmentally regulated shape change. We found that the volume of the macronucleus increases during coalescence, suggesting an inflation-based mechanism. When the nuclear transport factor, CSE1, is knocked down by RNAi, the shape and volume changes of the macronucleus are attenuated, and nuclear morphology is altered. CSE1 protein undergoes a dynamic relocalization correlated with nuclear shape changes, being mainly cytoplasmic prior to nuclear coalescence, and accumulating inside the macronucleus during coalescence. At the end of regeneration, CSE1 protein levels are reduced as the macronucleus returns to its pre-coalescence volume. We propose a model in which nuclear transport via CSE1 is required to increase the volume of the macronucleus, thereby decreasing the surface-to-volume ratio and driving coalescence of the nodes into a single mass

The nuclear transport factor CSE1 drives macronuclear volume increase and macronuclear node coalescence in Stentor coeruleus

Summary: Stentor coeruleus provides a unique opportunity to study how cells regulate nuclear shape because its macronucleus undergoes a rapid, dramatic, and developmentally regulated shape change. We found that the volume of the macronucleus increases during coalescence, suggesting an inflation-based mechanism. When the nuclear transport factor, CSE1, is knocked down by RNAi, the shape and volume changes of the macronucleus are attenuated, and nuclear morphology is altered. CSE1 protein undergoes a dynamic relocalization correlated with nuclear shape changes, being mainly cytoplasmic prior to nuclear coalescence, and accumulating inside the macronucleus during coalescence. At the end of regeneration, CSE1 protein levels are reduced as the macronucleus returns to its pre-coalescence volume. We propose a model in which nuclear transport via CSE1 is required to increase the volume of the macronucleus, thereby decreasing the surface-to-volume ratio and driving coalescence of the nodes into a single mass

Distribution of pairwise Rhodopsin expression.

<p>(A & B) Each point corresponds to a single PR, with the two coordinates giving the relative expression levels of two Rhodopsins. Data was pooled across all replicates at each time point. To give a sense for the density of points in different regions, each point was colored to indicate the number of points within a radius = 0.5 around it. The color bar shows the number of points indicated by each color.</p

Bimodal expression of Rh6 in R8 cells.

<p>The distribution of Rh6 levels in R8 cells shown here represents retinae at all time points. The bar graph indicates the probability density of all PRs in each expression level bin. A bimodal distribution, given by a mixture of two normal distributions, was fit to the data using maximum likelihood fitting. The means (μ) and standard deviations (σ) of the two Gaussians are shown, and the mixture proportion is such that 80% of cells express Rh6 at high levels, while 20% express Rh6 at low levels.</p

Rh3, Rh5 and Rh6 are de-repressed in <i>dve</i> mutants.

<p>(A) Three dimensional rendering of a representative confocal stack of a retina dissected at the 2 week developmental time point. Phalloidin, which stains actin, was used to visualize the rhabdomeres (green). This retina is co-stained for Rh5 (red) and Rh6 (blue). The inset shown is a zoomed-in view of the center of the retina. (B & C) Retinae were co-stained for two Rhodopsins, and representative ommatidia extracted automatically from the image stacks are shown for retinae co-stained for either Rh3–Rh6 or Rh5–Rh6 (panels B-i & C-i). Panels B-ii & C-ii show a cross section of the ommatidium in the phalloidin channel, indicating the automatically identified PR cells (R1–R6; R7/R8). Rh3 levels exhibit de-repression in outer PR cells (B-iii). Rh6 levels exhibit de-repression in outer PR cells (panels B-iv & C-iv). Rh5 levels exhibit de-repression in outer PR cells (C-iii). Scale bar is 1.5 µm (panels B) and 1.0 µm (panels C).</p

Best-fit parameters for two-state model of gene expression.

<p>All fits were performed using maximum likelihood optimization (we used <i>Mathematica 8</i> to perform the fitting). The functional form of the fit consisted of a linear combination of two gamma distribution pdfs, denoted and , with the mixture parameter . The pdf for a gamma distribution is defined by . The pdf is shifted by Δ<i>x</i>, determined by the lowest levels detected in each experiment: . The pdf is shifted to the mode of the pdf: . The mixture pdf is given by .</p

Rhodopsin distributions in photoreceptors fit to a two-state gene expression model.

<p>Data pooled across photoreceptors is shown in bars. The fit to the two-state model, , given in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002357#pcbi-1002357-t001" target="_blank">Table 1</a>, is shown in magenta; the component corresponding to the on state, , is shown in cyan. Densities and are integrated over each bin before plotting to allow comparison with the bar histograms. Insets show data from wild-type retinae, and the fit to a single gamma distribution function (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002357#pcbi-1002357-t001" target="_blank">Table 1</a>) is shown in magenta.</p