An incremental approach to automated protein localisation

Tscherepanow M, Jensen N, Kummert F. An incremental approach to automated protein localisation. BMC Bioinformatics. 2008;9(1): 445.Background: The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected. Results: We introduce a novel approach to automated protein localisation in living cells. In contrast to well-known techniques, the protein localisation technique presented in this article aims at combining the two types of approaches described above: After an automatic identification of unknown protein locations, a potential user is enabled to incorporate them into the pre-trained system. An incremental neural network allows the classification of a fixed set of protein location as well as the detection, clustering and incorporation of additional patterns that occur during an experiment. Here, the proposed technique achieves promising results with respect to both tasks. In addition, the protein localisation procedure has been adapted to an existing cell recognition approach. Therefore, it is especially well-suited for high-throughput investigations where user interactions have to be avoided. Conclusion: We have shown that several aspects required for developing an automatic protein localisation technique – namely the recognition of cells, the classification of protein distribution patterns into a set of learnt protein locations, and the detection and learning of new locations – can be combined successfully. So, the proposed method constitutes a crucial step to render image-based protein localisation techniques amenable to large-scale experiments

Cadophora margaritata sp. nov. and other fungi associated with the longhorn beetles Anoplophora glabripennis and Saperda carcharias in Finland

Symbiosis with microbes is crucial for survival and development of wood-inhabiting longhorn beetles (Coleoptera: Cerambycidae). Thus, knowledge of the endemic fungal associates of insects would facilitate risk assessment in cases where a new invasive pest occupies the same ecological niche. However, the diversity of fungi associated with insects remains poorly understood. The aim of this study was to investigate fungi associated with the native large poplar longhorn beetle (Saperda carcharias) and the recently introduced Asian longhorn beetle (Anoplophora glabripennis) infesting hardwood trees in Finland. We studied the cultivable fungal associates obtained from Populus tremula colonised by S. carcharias, and Betula pendula and Salix caprea infested by A. glabripennis, and compared these to the samples collected from intact wood material. This study detected a number of plant pathogenic and saprotrophic fungi, and species with known potential for enzymatic degradation of wood components. Phylogenetic analyses of the most commonly encountered fungi isolated from the longhorn beetles revealed an association with fungi residing in the Cadophora-Mollisia species complex. A commonly encountered fungus was Cadophora spadicis, a recently described fungus associated with wood-decay. In addition, a novel species of Cadophora, for which the name Cadophora margaritata sp. nov. is provided, was isolated from the colonised wood.Peer reviewe

Animal-associated fungi : editorial

Of 1882 fungal species described in 2019, only 3.5% were animal-associated. This percentage is representative of the poor understanding we have of this group of fungi, which are ephemeral, sometimes inconspicuous, and difficult to access, while often requiring specialized methods for their study. Following a two-session symposium on animal-associated fungi during the 2019 Annual Meeting of the Mycological Society of America, this special issue presents the work of 61 researchers in 16 countries. Twelve articles cover animal-associated fungi among Ascomycota, Basidiomycota, and Neocallimastigomycota—describing 29 new species, presenting new evolutionary hypotheses, and unearthing new ecological data