Myoinhibitory peptide regulates feeding in the marine annelid Platynereis

BACKGROUND: During larval settlement and metamorphosis, marine invertebrates undergo changes in habitat, morphology, behavior and physiology. This change between life-cycle stages is often associated with a change in diet or a transition between a non-feeding and a feeding form. How larvae regulate changes in feeding during this life-cycle transition is not well understood. Neuropeptides are known to regulate several aspects of feeding, such as food search, ingestion and digestion. The marine annelid Platynereis dumerilii has a complex life cycle with a pelagic non-feeding larval stage and a benthic feeding postlarval stage, linked by the process of settlement. The conserved neuropeptide myoinhibitory peptide (MIP) is a key regulator of larval settlement behavior in Platynereis. Whether MIP also regulates the initiation of feeding, another aspect of the pelagic-to-benthic transition in Platynereis, is currently unknown. RESULTS: Here, we explore the contribution of MIP to the regulation of feeding behavior in settled Platynereis postlarvae. We find that in addition to expression in the brain, MIP is expressed in the gut of developing larvae in sensory neurons that densely innervate the hindgut, the foregut, and the midgut. Activating MIP signaling by synthetic neuropeptide addition causes increased gut peristalsis and more frequent pharynx extensions leading to increased food intake. Conversely, morpholino-mediated knockdown of MIP expression inhibits feeding. In the long-term, treatment of Platynereis postlarvae with synthetic MIP increases growth rate and results in earlier cephalic metamorphosis. CONCLUSIONS: Our results show that MIP activates ingestion and gut peristalsis in Platynereis postlarvae. MIP is expressed in enteroendocrine cells of the digestive system suggesting that following larval settlement, feeding may be initiated by a direct sensory-neurosecretory mechanism. This is similar to the mechanism by which MIP induces larval settlement. The pleiotropic roles of MIP may thus have evolved by redeploying the same signaling mechanism in different aspects of a life-cycle transition. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12983-014-0093-6) contains supplementary material, which is available to authorized users

Object-based representation and analysis of light and electron microscopic volume data using Blender

This is the final version of the article. Available from the publisher via the DOI in this record.BACKGROUND: Rapid improvements in light and electron microscopy imaging techniques and the development of 3D anatomical atlases necessitate new approaches for the visualization and analysis of image data. Pixel-based representations of raw light microscopy data suffer from limitations in the number of channels that can be visualized simultaneously. Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze. RESULTS: Here we exploit the advanced visualization capabilities and flexibility of the open-source platform Blender to visualize and analyze anatomical atlases. We use light-microscopy-based gene expression atlases and electron microscopy connectome volume data from larval stages of the marine annelid Platynereis dumerilii. We build object-based larval gene expression atlases in Blender and develop tools for annotation and coexpression analysis. We also represent and analyze connectome data including neuronal reconstructions and underlying synaptic connectivity. CONCLUSIONS: We demonstrate the power and flexibility of Blender for visualizing and exploring complex anatomical atlases. The resources we have developed for Platynereis will facilitate data sharing and the standardization of anatomical atlases for this species. The flexibility of Blender, particularly its embedded Python application programming interface, means that our methods can be easily extended to other organisms.The research leading to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/European Research Council Grant Agreement 260821

Chemical crosslinking and mass spectrometry to elucidate the topology of integral membrane proteins.

Here we made an attempt to obtain partial structural information on the topology of multispan integral membrane proteins of yeast by isolating organellar membranes, removing peripheral membrane proteins at pH 11.5 and introducing chemical crosslinks between vicinal amino acids either using homo- or hetero-bifunctional crosslinkers. Proteins were digested with specific proteases and the products analysed by mass spectrometry. Dedicated software tools were used together with filtering steps optimized to remove false positive crosslinks. In proteins of known structure, crosslinks were found only between loops residing on the same side of the membrane. As may be expected, crosslinks were mainly found in very abundant proteins. Our approach seems to hold to promise to yield low resolution topological information for naturally very abundant or strongly overexpressed proteins with relatively little effort. Here, we report novel XL-MS-based topology data for 17 integral membrane proteins (Akr1p, Fks1p, Gas1p, Ggc1p, Gpt2p, Ifa38p, Ist2p, Lag1p, Pet9p, Pma1p, Por1p, Sct1p, Sec61p, Slc1p, Spf1p, Vph1p, Ybt1p)

CWH43 is required for the introduction of ceramides into GPI anchors in Saccharomyces cerevisiae

After glycosylphosphatidylinositols (GPIs) are added to GPI proteins of Saccharomyces cerevisiae, the fatty acid in sn-2 of the diacylglycerol moiety can be replaced by a C26:0 fatty acid by a deacylation–reacylation cycle catalysed by Per1p and Gup1p. Furthermore the diacylglycerol moiety of the yeast GPI anchor can also be replaced by ceramides. CWH43 of yeast is homologous to PGAP2, a gene that recently was implicated in a similar deacylation reacylation cycle of GPI proteins in mammalian cells, where PGAP2 is required for the reacylation of monoradylglycerol-type GPI anchors. Here we show that mutants lacking CWH43 are unable to synthesize ceramide-containing GPI anchors, while the replacement of C18 by C26 fatty acids on the primary diacylglycerol anchor by Per1p and Gup1p is still intact. CWH43 contains the COG3568 metal hydrolase motif, which is found in many eukaryotic and prokaryotic enzymes. The conserved His 802 residue of this motif was identified as being essential for ceramide remodelling. Ceramide remodelling is not required for the normal integration of GPI proteins into the cell wall. All remodelling reactions are dependent on prior removal of the inositol-linked fatty acid by Bst1p

The Market Viability of Nuclear Hydrogen Technologies.

The Department of Energy Office of Nuclear Energy is supporting system studies to gain a better understanding of nuclear power's potential role in a hydrogen economy and what hydrogen production technologies show the most promise. This assessment includes identifying commercial hydrogen applications and their requirements, comparing the characteristics of nuclear hydrogen systems to those market requirements, evaluating nuclear hydrogen configuration options within a given market, and identifying the key drivers and thresholds for market viability of nuclear hydrogen options. One of the objectives of the current analysis phase is to determine how nuclear hydrogen technologies could evolve under a number of different futures. The outputs of our work will eventually be used in a larger hydrogen infrastructure and market analysis conducted for DOE-EE using a system-level market simulation tool now underway. This report expands on our previous work by moving beyond simple levelized cost calculations and looking at profitability, risk, and uncertainty from an investor's perspective. We analyze a number of technologies and quantify the value of certain technology and operating characteristics. Our model to assess the profitability of the above technologies is based on Real Options Theory and calculates the discounted profits from investing in each of the production facilities. We use Monte-Carlo simulations to represent the uncertainty in hydrogen and electricity prices. The model computes both the expected value and the distribution of discounted profits from a production plant. We also quantify the value of the option to switch between hydrogen and electricity production in order to maximize investor profits. Uncertainty in electricity and hydrogen prices can be represented with two different stochastic processes: Geometric Brownian Motion (GBM) and Mean Reversion (MR). Our analysis finds that the flexibility to switch between hydrogen and electricity leads to significantly different results in regards to the relative profitability of the different technologies and configurations. This is the case both with a deterministic and a stochastic analysis, as shown in the tables below. The flexibility in output products clearly adds substantial value to the HPE-ALWR and HTE-HTGR plants. In fact, under the GBM assumption for prices, the HTE-HTGR plant becomes more profitable than the SI-HTGR configuration, although SI-HTGR has a much lower levelized cost. For the HTE-HTGR plant it is also profitable to invest in additional electric turbine capacity (Case b) in order to fully utilize the heat from the nuclear reactor for electricity production when this is more profitable than producing hydrogen. The technologies are all at the research and development stage, so there are significant uncertainties regarding the technology cost and performance assumptions used in this analysis. As the technologies advance, the designers need to refine the cost and performance evaluation to provide a more reliable set of input for a more rigorous analysis. In addition, the durability of the catalytic activity of the materials at the hydrogen plant during repetitive price cycling is of prime importance concerning the flexibility of switching from hydrogen to electricity production. However, given the potential significant economic benefit that can be brought from cogeneration with the flexibility to quickly react to market signals, DOE should consider R&D efforts towards developing durable materials and processes that can enable this type of operation. Our future work will focus on analyzing a range of hydrogen production technologies associated with an extension of the financial analysis framework presented here. We are planning to address a variety of additional risks and options, such as the value of modular expansion in addition to the co-generation capability (i.e., a modular increase in the hydrogen production capacity of a plant in a given market with rising hydrogen demand), and contrast that with economies-of-scale of large-unit designs