Functional coupling of microtubules to membranes - implications for membrane structure and dynamics

The microtubule network dictates much of the spatial patterning of the cytoplasm, and the coupling of microtubules to membranes controls the structure and positioning of organelles and directs membrane trafficking between them. The connection between membranes and the microtubule cytoskeleton, and the way in which organelles are shaped and moved by interactions with the cytoskeleton, have been studied intensively in recent years. In particular, recent work has expanded our thinking of this topic to include the mechanisms by which membranes are shaped and how cargo is selected for trafficking as a result of coupling to the cytoskeleton. In this Commentary, I will discuss the molecular basis for membrane–motor coupling and the physiological outcomes of this coupling, including the way in which microtubule-based motors affect membrane structure, cargo sorting and vectorial trafficking between organelles. Whereas many core concepts of these processes are now well understood, key questions remain about how the coupling of motors to membranes is established and controlled, about the regulation of cargo and/or motor loading and about the control of directionality.</jats:p

Membrane contact sites - an interesting species, an interesting mix

In this issue of EMBO reports, Loewen and colleagues reveal a role for plasma membrane–endoplasmic reticulum contact sites in regulating phosphatidylcholine synthesis in budding yeast

Energy consumption and cooperation for optimal sensing

The reliable detection of environmental molecules in the presence of noise is an important cellular function, yet the underlying computational mechanisms are not well understood. We introduce a model of two interacting sensors which allows for the principled exploration of signal statistics, cooperation strategies and the role of energy consumption in optimal sensing, quantified through the mutual information between the signal and the sensors. Here we report that in general the optimal sensing strategy depends both on the noise level and the statistics of the signals. For joint, correlated signals, energy consuming (nonequilibrium), asymmetric couplings result in maximum information gain in the low-noise, high-signal-correlation limit. Surprisingly we also find that energy consumption is not always required for optimal sensing. We generalise our model to incorporate time integration of the sensor state by a population of readout molecules, and demonstrate that sensor interaction and energy consumption remain important for optimal sensing.Comment: 9 pages, 5 figures, Forthcoming in Nature Communication

Early stages of retinal development depend on Sec13 function

Summary ER-to-Golgi transport of proteins destined for the extracellular space or intracellular compartments depends on the COPII vesicle coat and is constitutive in all translationally active cells. Nevertheless, there is emerging evidence that this process is regulated on a cell- and tissue-specific basis, which means that components of the COPII coat will be of differential importance to certain cell types. The COPII coat consists of an inner layer, Sec23/24 and an outer shell, Sec13/31. We have shown previously that knock-down of Sec13 results in concomitant loss of Sec31. In zebrafish and cultured human cells this leads to impaired trafficking of large cargo, namely procollagens, and is causative for defects in craniofacial and gut development. It is now widely accepted that the outer COPII coat is key to the architecture and stability of ER export vesicles containing large, unusual cargo proteins. Here, we investigate zebrafish eye development following Sec13 depletion. We find that photoreceptors degenerate or fail to develop from the onset. Impaired collagen trafficking from the retinal pigment epithelium and defects in overall retinal lamination also seen in Sec13-depleted zebrafish might have been caused by increased apoptosis and reduced topical proliferation in the retina. Our data show that the outer layer of the COPII coat is also necessary for the transport of large amounts of cargo proteins, in this case rhodopsin, rather than just large cargo as previously thought

The impact of uncertainty in satellite data on the assessment of flood inundation models

The performance of flood inundation models is often assessed using satellite observed data; however these data have inherent uncertainty. In this study we assess the impact of this uncertainty when calibrating a flood inundation model (LISFLOOD-FP) for a flood event in December 2006 on the River Dee, North Wales, UK. The flood extent is delineated from an ERS-2 SAR image of the event using an active contour model (snake), and water levels at the flood margin calculated through intersection of the shoreline vector with LiDAR topographic data. Gauged water levels are used to create a reference water surface slope for comparison with the satellite-derived water levels. Residuals between the satellite observed data points and those from the reference line are spatially clustered into groups of similar values. We show that model calibration achieved using pattern matching of observed and predicted flood extent is negatively influenced by this spatial dependency in the data. By contrast, model calibration using water elevations produces realistic calibrated optimum friction parameters even when spatial dependency is present. To test the impact of removing spatial dependency a new method of evaluating flood inundation model performance is developed by using multiple random subsamples of the water surface elevation data points. By testing for spatial dependency using Moran’s I, multiple subsamples of water elevations that have no significant spatial dependency are selected. The model is then calibrated against these data and the results averaged. This gives a near identical result to calibration using spatially dependent data, but has the advantage of being a statistically robust assessment of model performance in which we can have more confidence. Moreover, by using the variations found in the subsamples of the observed data it is possible to assess the effects of observational uncertainty on the assessment of flooding risk

Epithelial organization and cyst lumen expansion require efficient Sec13-Sec31-driven secretion

Epithelial morphogenesis is directed by interactions with the underlying extracellular matrix. Secretion of collagen and other matrix components requires efficient coat complex II (COPII) vesicle formation at the endoplasmic reticulum. Here, we show that suppression of the outer layer COPII component, Sec13, in zebrafish embryos results in a disorganized gut epithelium. In human intestinal epithelial cells (Caco-2), Sec13 depletion causes defective epithelial polarity and organization on permeable supports. Defects are seen in the ability of cells to adhere to the substrate, form a monolayer and form intercellular junctions. When embedded in a three-dimensional matrix, Sec13-depleted Caco-2 cells form cysts but, unlike controls, are defective in lumen expansion. Incorporation of primary fibroblasts within the three-dimensional culture substantially restores normal morphogenesis. We conclude that efficient COPII-dependent secretion, notably assembly of Sec13–Sec31, is required to drive epithelial morphogenesis in both two- and three-dimensional cultures in vitro, as well as in vivo. Our results provide insight into the role of COPII in epithelial morphogenesis and have implications for the interpretation of epithelial polarity and organization assays in cell culture

A hierarchical Bayesian model for predicting ecological interactions using scaled evolutionary relationships

Identifying undocumented or potential future interactions among species is a challenge facing modern ecologists. Recent link prediction methods rely on trait data, however large species interaction databases are typically sparse and covariates are limited to only a fraction of species. On the other hand, evolutionary relationships, encoded as phylogenetic trees, can act as proxies for underlying traits and historical patterns of parasite sharing among hosts. We show that using a network-based conditional model, phylogenetic information provides strong predictive power in a recently published global database of host-parasite interactions. By scaling the phylogeny using an evolutionary model, our method allows for biological interpretation often missing from latent variable models. To further improve on the phylogeny-only model, we combine a hierarchical Bayesian latent score framework for bipartite graphs that accounts for the number of interactions per species with the host dependence informed by phylogeny. Combining the two information sources yields significant improvement in predictive accuracy over each of the submodels alone. As many interaction networks are constructed from presence-only data, we extend the model by integrating a correction mechanism for missing interactions, which proves valuable in reducing uncertainty in unobserved interactions.Comment: To appear in the Annals of Applied Statistic