The role of interfacial lipids in stabilizing membrane protein oligomers

Oligomerization of membrane proteins in response to lipid binding has a critical role in many cell-signalling pathways1 but is often difficult to define2 or predict3. Here we report the development of a mass spectrometry platform to determine simultaneously the presence of interfacial lipids and oligomeric stability and to uncover how lipids act as key regulators of membrane-protein association. Evaluation of oligomeric strength for a dataset of 125 α-helical oligomeric membrane proteins reveals an absence of interfacial lipids in the mass spectra of 12 membrane proteins with high oligomeric stability. For the bacterial homologue of the eukaryotic biogenic transporters (LeuT4, one of the proteins with the lowest oligomeric stability), we found a precise cohort of lipids within the dimer interface. Delipidation, mutation of lipid-binding sites or expression in cardiolipin-deficient Escherichia coli abrogated dimer formation. Molecular dynamics simulation revealed that cardiolipin acts as a bidentate ligand, bridging across subunits. Subsequently, we show that for the Vibrio splendidus sugar transporter SemiSWEET5, another protein with low oligomeric stability, cardiolipin shifts the equilibrium from monomer to functional dimer. We hypothesized that lipids are essential for dimerization of the Na+/H+ antiporter NhaA from E. coli, which has the lowest oligomeric strength, but not for the substantially more stable homologous Thermus thermophilus protein NapA. We found that lipid binding is obligatory for dimerization of NhaA, whereas NapA has adapted to form an interface that is stable without lipids. Overall, by correlating interfacial strength with the presence of interfacial lipids, we provide a rationale for understanding the role of lipids in both transient and stable interactions within a range of α-helical membrane proteins, including G-protein-coupled receptors

Generation of Up to Date Land Cover Maps for Central Asia

Human activity and climate variability has always changed the Earth’s surface and both will mainly contribute to future alteration in land cover and land use changes. In this chapte we demonstrate a land cover and land use classification approach for Central Asia addressing regional characteristics of the study area. With the aim of regional classification map for Central Asia a specific classification scheme based on the Land Cover Classification System (LCCS) of the Food and Agriculture Organisation of the United Nations Environment Programme (FAO-UNEP) was developed. The classification was performed by using a supervised classification method applied on metrics, which were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data with 250 m spatial resolution. The metrics wer derived from annual time-series of red and nearinfrared reflectance as well as from Normalized Difference Vegetation Index (NDVI) and thus reflect the temporal behavior of different land cover types. Reference data required for a supervised classification approach were collected from several high resolution satellite imagery distributed all over the study area. The overall accuracy results for performed classification of the year 2001 and 2009 are 91.2 and 91.3 %. The comparison of both classification maps shows significant alterations for different classes. Water bodies such as Shardara Water Reservoir and Aral Sea have changed in their extent. Whereby, the size of the Shardara Water Reservoir is very dynamic from year to year due to water management and the eastern lobe of southern Aral Sea has decreased because of the lack of inflow from Amu Darja. Furthermore, some large scale changes were detected in sparsely vegetated areas in Turkmenistan, where spring precipitation mainly affects the vegetation density. In the north of Kazakhstan significant forest losses caused by forest fires and logging were detected. The presented classification approach is a suitable tool for monitoring land cover and land use in Central Asia. Such independent information is important for accurate assessment of water and land recourses

The fish fauna of Ampère Seamount (NE Atlantic) and the adjacent abyssal plain

An inventory of benthic and benthopelagic fishes is presented as a result of two exploratory surveys around Ampe`re Seamount, between Madeira and the Portuguese mainland, covering water depths from 60 to 4,400 m. A total of 239 fishes were collected using different types of sampling gear. Three chondrichthyan species and 31 teleosts in 21 families were identified. The collections showed a vertical zonation with little overlap, but indications for an affinity of species to certain water masses were only vague. Although most of the species present new records for Ampe`re Seamount, all of them have been known for the NE Atlantic; endemic species were not found. The comparison with fish communities at other NE Atlantic seamounts indicates that despite a high ichthyofaunal similarity, which supports the ‘‘stepping stone’’ hypothesis of species dispersal, some differences can be attributed to the local features of the seamounts.info:eu-repo/semantics/publishedVersio

How Computational Models Enable Mechanistic Insights into Virus Infection

An implicit aim in cellular infection biology is to understand the mechanisms how viruses, microbes, eukaryotic parasites, and fungi usurp the functions of host cells and cause disease. Mechanistic insight is a deep understanding of the biophysical and biochemical processes that give rise to an observable phenomenon. It is typically subject to falsification, that is, it is accessible to experimentation and empirical data acquisition. This is different from logic and mathematics, which are not empirical, but built on systems of inherently consistent axioms. Here, we argue that modeling and computer simulation, combined with mechanistic insights, yields unprecedented deep understanding of phenomena in biology and especially in virus infections by providing a way of showing sufficiency of a hypothetical mechanism. This ideally complements the necessity statements accessible to empirical falsification by additional positive evidence. We discuss how computational implementations of mathematical models can assist and enhance the quantitative measurements of infection dynamics of enveloped and non-enveloped viruses and thereby help generating causal insights into virus infection biology