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Background: Aedes albopictus and Ae. japonicus are two of the most widespread invasive mosquito species that have recently become established in western Europe. Both species are associated with the transmission of a number of serious diseases and are projected to continue their spread in Europe.
Methods: In the present study, we modelled the habitat suitability for both species under current and future climatic conditions by means of an Ensemble forecasting approach. We additionally compared the modelled MAXENT niches of Ae. albopictus and Ae. japonicus regarding temperature and precipitation requirements.
Results: Both species were modelled to find suitable habitat conditions in distinct areas within Europe: Ae. albopictus within the Mediterranean regions in southern Europe, Ae. japonicus within the more temperate regions of central Europe. Only in few regions, suitable habitat conditions were projected to overlap for both species. Whereas Ae. albopictus is projected to be generally promoted by climate change in Europe, the area modelled to be climatically suitable for Ae. japonicus is projected to decrease under climate change. This projection of range reduction under climate change relies on the assumption that Ae. japonicus is not able to adapt to warmer climatic conditions. The modelled MAXENT temperature niches of Ae. japonicus were found to be narrower with an optimum at lower temperatures compared to the niches of Ae. albopictus.
Conclusions: Species distribution models identifying areas with high habitat suitability can help improving monitoring programmes for invasive species currently in place. However, as mosquito species are known to be able to adapt to new environmental conditions within the invasion range quickly, niche evolution of invasive mosquito species should be closely followed upon in future studies.
Core Facilities (CF) for advanced light microscopy (ALM) have become indispensable support units for research in the life sciences. Their organizational structure and technical characteristics are quite diverse, although the tasks they pursue and the services they offer are similar. Therefore, throughout Europe, scientists from ALM‐CFs are forming networks to promote interactions and discuss best practice models. Here, we present recommendations for ALM‐CF operations elaborated by the workgroups of the German network of ALM‐CFs, German Bio‐Imaging (GerBI). We address technical aspects of CF planning and instrument maintainance, give advice on the organization and management of an ALM‐CF, propose a scheme for the training of CF users, and provide an overview of current resources for image processing and analysis. Further, we elaborate on the new challenges and opportunities for professional development and careers created by CFs. While some information specifically refers to the German academic system, most of the content of this article is of general interest for CFs in the life sciences.
50 years of amino acid hydrophobicity scales : revisiting the capacity for peptide classification
(2016)
Background: Physicochemical properties are frequently analyzed to characterize protein-sequences of known and unknown function. Especially the hydrophobicity of amino acids is often used for structural prediction or for the detection of membrane associated or embedded β-sheets and α-helices. For this purpose many scales classifying amino acids according to their physicochemical properties have been defined over the past decades. In parallel, several hydrophobicity parameters have been defined for calculation of peptide properties. We analyzed the performance of separating sequence pools using 98 hydrophobicity scales and five different hydrophobicity parameters, namely the overall hydrophobicity, the hydrophobic moment for detection of the α-helical and β-sheet membrane segments, the alternating hydrophobicity and the exact ß-strand score.
Results: Most of the scales are capable of discriminating between transmembrane α-helices and transmembrane β-sheets, but assignment of peptides to pools of soluble peptides of different secondary structures is not achieved at the same quality. The separation capacity as measure of the discrimination between different structural elements is best by using the five different hydrophobicity parameters, but addition of the alternating hydrophobicity does not provide a large benefit. An in silico evolutionary approach shows that scales have limitation in separation capacity with a maximal threshold of 0.6 in general. We observed that scales derived from the evolutionary approach performed best in separating the different peptide pools when values for arginine and tyrosine were largely distinct from the value of glutamate. Finally, the separation of secondary structure pools via hydrophobicity can be supported by specific detectable patterns of four amino acids.
Conclusion: It could be assumed that the quality of separation capacity of a certain scale depends on the spacing of the hydrophobicity value of certain amino acids. Irrespective of the wealth of hydrophobicity scales a scale separating all different kinds of secondary structures or between soluble and transmembrane peptides does not exist reflecting that properties other than hydrophobicity affect secondary structure formation as well. Nevertheless, application of hydrophobicity scales allows distinguishing between peptides with transmembrane α-helices and β-sheets. Furthermore, the overall separation capacity score of 0.6 using different hydrophobicity parameters could be assisted by pattern search on the protein sequence level for specific peptides with a length of four amino acids.