Lipid-Protein Interactions Are Unique Fingerprints for Membrane Proteins

Cell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Our current understanding of the detailed organization of cell membranes remains rather elusive, because of the challenge to study fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of 10 different membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between the leaflets. The simulations detail how each protein modulates its local lipid environment in a unique way, through enrichment or depletion of specific lipid components, resulting in thickness and curvature gradients. Our results provide a molecular glimpse of the complexity of lipid-protein interactions, with potentially far-reaching implications for our understanding of the overall organization of real cell membranes

Emerging Diversity in Lipid-Protein Interactions

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid-protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid-protein interactions, and to link lipid-protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid-protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid-protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid-protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid-protein interactions

Of the importance of a leaf: the ethnobotany of sarma in Turkey and the Balkans

BACKGROUND: Sarma - cooked leaves rolled around a filling made from rice and/or minced meat, possibly vegetables and seasoning plants - represents one of the most widespread feasting dishes of the Middle Eastern and South-Eastern European cuisines. Although cabbage and grape vine sarma is well-known worldwide, the use of alternative plant leaves remains largely unexplored. The aim of this research was to document all of the botanical taxa whose leaves are used for preparing sarma in the folk cuisines of Turkey and the Balkans. Methods: Field studies were conducted during broader ethnobotanical surveys, as well as during ad-hoc investigations between the years 2011 and 2014 that included diverse rural communities in Croatia, Bosnia and Herzegovina, Serbia, Kosovo, Albania, Macedonia, Bulgaria, Romania, and Turkey. Primary ethnobotanical and folkloric literatures in each country were also considered. Results: Eighty-seven botanical taxa, mainly wild, belonging to 50 genera and 27 families, were found to represent the bio-cultural heritage of sarma in Turkey and the Balkans. The greatest plant biodiversity in sarma was found in Turkey and, to less extent, in Bulgaria and Romania. The most commonly used leaves for preparing sarma were those of cabbage (both fresh and lacto-fermented), grape vine, beet, dock, sorrel, horseradish, lime tree, bean, and spinach. In a few cases, the leaves of endemic species (Centaurea haradjianii, Rumex gracilescens, and R. olympicus in Turkey) were recorded. Other uncommon sarma preparations were based on lightly toxic taxa, such as potato leaves in NE Albania, leaves of Arum, Convolvulus, and Smilax species in Turkey, of Phytolacca americana in Macedonia, and of Tussilago farfara in diverse countries. Moreover, the use of leaves of the introduced species Reynoutria japonica in Romania, Colocasia esculenta in Turkey, and Phytolacca americana in Macedonia shows the dynamic nature of folk cuisines. Conclusion: The rich ethnobotanical diversity of sarma confirms the urgent need to record folk culinary plant knowledge. The results presented here can be implemented into initiatives aimed at re-evaluating folk cuisines and niche food markets based on local neglected ingredients, and possibly also to foster trajectories of the avant-garde cuisines inspired by ethnobotanical knowledge

The bear in Eurasian plant names: Motivations and models

Ethnolinguistic studies are important for understanding an ethnic group's ideas on the world, expressed in its language. Comparing corresponding aspects of such knowledge might help clarify problems of origin for certain concepts and words, e.g. whether they form common heritage, have an independent origin, are borrowings, or calques. The current study was conducted on the material in Slavonic, Baltic, Germanic, Romance, Finno-Ugrian, Turkic and Albanian languages. The bear was chosen as being a large, dangerous animal, important in traditional culture, whose name is widely reflected in folk plant names. The phytonyms for comparison were mostly obtained from dictionaries and other publications, and supplemented with data from databases, the co-authors' field data, and archival sources (dialect and folklore materials). More than 1200 phytonym use records (combinations of a local name and a meaning) for 364 plant and fungal taxa were recorded to help find out the reasoning behind bear-nomination in various languages, as well as differences and similarities between the patterns among them. Among the most common taxa with bear-related phytonyms were Arctostaphylos uva-ursi (L.) Spreng., Heracleum sphondylium L., Acanthus mollis L., and Allium ursinum L., with Latin loan translation contributing a high proportion of the phytonyms. Some plants have many and various bear-related phytonyms, while others have only one or two bear names. Features like form and/or surface generated the richest pool of names, while such features as colour seemed to provoke rather few associations with bears. The unevenness of bear phytonyms in the chosen languages was not related to the size of the language nor the present occurence of the Brown Bear in the region. However, this may, at least to certain extent, be related to the amount of the historical ethnolinguistic research done on the selected languages

Elucidating the Interplay Between Lipids and Membrane Proteins Using Multiscale Computer Simulations

Biological membranes are complex cellular structures formed by a large number of different lipid types, that also contain a variety of bound proteins, carbohydrates, and other molecules. The detailed orchestration of all these elements has been a major focus of scientific research during the last 5 decades. Computer-based methods, such as molecular dynamics (MD) simulations, have proven to be a valuable approach in addressing many of the details of lipid organization and membrane protein activity. I used MD simulations at both atomistic and coarse-grained level of detail to study the number of way lipids and proteins interact and their possible functional ramifications. In part of my work, I studied the interaction of G Protein-Coupled Receptors (GPCRs) with lipids at a family-wide level. Plenty of other computational studies had shown specific lipid-protein interactions for a handful of GPCRs but with quite different outcomes on their number, location, and lipid identity. In my work, I simulated 28 different GPCR structures and showed that they are distinguished by a unique interaction profile with membrane lipids. I provided a comprehensive analysis of simulation results with available crystallographic data. I also studied the lipid-protein interaction profile of AMPA receptors and cyclooxygenases (mainly COX-1), showing that they both form specific interactions with lipids, but do so in a quite different fashion. AMPA receptors interact specifically with diacylglycerol lipids, whereas COX-1 enzymes do so indiscriminately with glycerophospholipids, cholesterol, and fatty acids, but at different levels of interaction strength. Using atomistic simulations, we show the binding pathway of arachidonic acid to COX-1 and identify a series of arginine residues that guide it toward the hydrophobic cavity of the enzyme. As part of my work, I also developed a webserver that automates the analysis and visualization of lipid-protein interactions from MD simulations allowing for the creation of automated pipelines to study lipid-protein interactions in the future. Lastly, I provide a short review of some of the main challenges facing the field along with possible solutions going forward. My work expands our understanding of lipid-protein interactions

Statisfy me: What are my stats?

The increasing adoption of the Linked Data format, RDF, over the last two decades has brought new opportunities. It has also raised new challenges though, especially when it comes to managing and processing large amounts of RDF data. In particular, assessing the internal structure of a data set is important, since it enables users to understand the data better. One prominent way of assessment is computing statistics about the instances and schema of a data set. However, computing statistics of large RDF data is computationally expensive. To overcome this challenging situation, we previously built DistLODStats, a framework for parallel calculation of 32 statistical criteria over large RDF datasets, based on Apache Spark. Running DistLODStats is, thus, done via submitting jobs to a Spark cluster. Often times, this process is done manually, either by connecting to the cluster machine or via a dedicated resource manager. This approach is inconvenient as it requires acquiring new software skills as well as the direct interaction of users with the cluster. In order to make the use of DistLODStats easier, we propose in this paper an approach for triggering RDF statistics remotely simply using HTTP requests. DistLODStats is built as a plugin into the larger SANSA Framework and makes use of Apache Livy, a novel lightweight solution for interacting with Spark cluster via a REST Interface

Insights into lipid-protein interactions from computer simulations

Lipid-protein interactions play an important direct role in the function of many membrane proteins. We argue they are key players in membrane structure, modulate membrane proteins in more subtle ways than direct binding, and are important for understanding the mechanism of classes of hydrophobic drugs. By directly comparing membrane proteins from different families in the same, complex lipid mixture, we found a unique lipid environment for every protein. Extending this work, we identified both differences and similarities in the lipid environment of GPCRs, dependent on which family they belong to and in some cases their conformational state, with particular emphasis on the distribution of cholesterol. More recently, we have been studying modes of coupling between protein conformation and local membrane properties using model proteins. In more applied approaches, we have used similar methods to investigate specific hypotheses on interactions of lipid and lipid-like molecules with ion channels. We conclude this perspective with some considerations for future work, including a new more sophisticated coarse-grained force field (Martini 3), an interactive visual exploration framework, and opportunities to improve sampling

Managing lifecycle of big data applications

The growing digitization and networking process within our society has a large influence on all aspects of everyday life. Large amounts of data are being produced continuously, and when these are analyzed and interlinked they have the potential to create new knowledge and intelligent solutions for economy and society. To process this data, we developed the Big Data Integrator (BDI) Platform with various Big Data components available out-of-the-box. The integration of the components inside the BDI Platform requires components homogenization, which leads to the standardization of the development process. To support these activities we created the BDI Stack Lifecycle (SL), which consists of development, packaging, composition, enhancement, deployment and monitoring steps. In this paper, we show how we support the BDI SL with the enhancement applications developed in the BDE project. As an evaluation, we demonstrate the applicability of the BDI SL on three pilots in the domains of transport, social sciences and security. © 2017, Springer International Publishing AG

Lipid–Protein Interactions Are Unique Fingerprints for Membrane Proteins

Cell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Our current understanding of the detailed organization of cell membranes remains rather elusive, because of the challenge to study fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of 10 different membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between the leaflets. The simulations detail how each protein modulates its local lipid environment in a unique way, through enrichment or depletion of specific lipid components, resulting in thickness and curvature gradients. Our results provide a molecular glimpse of the complexity of lipid–protein interactions, with potentially far-reaching implications for our understanding of the overall organization of real cell membranes