TY - JOUR A1 - Akhoundi, Mohammad A1 - Downing, Tim A1 - Votýpka, Jan A1 - Kuhls, Katrin A1 - Lukeš, Julius A1 - Cannet, Arnaud A1 - Ravel, Christophe A1 - Marty, Pierre A1 - Delaunay, Pascal A1 - Kasbari, Mohamed A1 - Granouillac, Bruno A1 - Gradoni, Luigi A1 - Sereno, Denis T1 - Leishmania infections: Molecular targets and diagnosis JF - Molecular Aspects of Medicine N2 - Progress in the diagnosis of leishmaniases depends on the development of effective methods and the discovery of suitable biomarkers. We propose firstly an update classification of Leishmania species and their synonymies. We demonstrate a global map highlighting the geography of known endemic Leishmania species pathogenic to humans. We summarize a complete list of techniques currently in use and discuss their advantages and limitations. The available data highlights the benefits of molecular markers in terms of their sensitivity and specificity to quantify variation from the subgeneric level to species complexes, (sub) species within complexes, and individual populations and infection foci. Each DNA-based detection method is supplied with a comprehensive description of markers and primers and proposal for a classification based on the role of each target and primer in the detection, identification and quantification of leishmaniasis infection. We outline a genome-wide map of genes informative for diagnosis that have been used for Leishmania genotyping. Furthermore, we propose a classification method based on the suitability of well-studied molecular markers for typing the 21 known Leishmania species pathogenic to humans. This can be applied to newly discovered species and to hybrid strains originating from inter-species crosses. Developing more effective and sensitive diagnostic methods and biomarkers is vital for enhancing Leishmania infection control programs. KW - molecular marker KW - diagnostic method KW - hybrid strain KW - sympatric species KW - genome-wide map Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9908 SN - 0098-2997 VL - 57 SP - 1 EP - 29 ER - TY - JOUR A1 - Wieland, Ralf A1 - Kuhls, Katrin A1 - Lentz, Hartmut H.K. A1 - Conraths, Franz A1 - Kampen, Helge A1 - Werner, Doreen T1 - Combined climate and regional mosquito habitat model based on machine learning JF - Ecological Modelling N2 - Besides invasive mosquito species also several native species are proven or suspected vectors of arboviruses as West Nile or Usutu virus in Western Europe. Habitat models of these native vectors can be a helpful tool for assessing the risk of autochthonous occurrence, outbreaks and spread of diseases caused by such arboviruses. Modelling native mosquitoes is complicated because of the perfect adaptation to the climatic and landscape conditions and their high abundance in contrast to invasive species. Here we present a new approach for such a habitat model for native mosquito species in Germany, which are considered as vectors of West Nile virus (WNV). Epizootic emergence of WNV was registered in Germany since 2018. The models are based on surveillance data of mosquitoes from the German citizen science project “Mückenatlas” complemented by data from systematic trap monitoring in Germany, and on data freely available from the Deutscher Wetterdienst (DWD) and OpenStreetMap (OSM). While climatic factors still play an important role, we could show that habitat suitability is predictable only by the combination of the climate model with a regional model. Both models were based on a machine-learning approach using XGBoost. Evaluation of the accuracy of the models was done by statistical analysis, determining among others feature importances using the SHAP-Library. Final output of the combined climatic and regional models are maps showing the superposed habitat suitability which are generated through a number of steps described in detail. These maps also include the registered cases of WNV infections in the selected region of Germany. KW - citizen science data KW - mosquito habitat modelling KW - machine learning KW - XGBoost KW - West Nile virus KW - vector borne disease Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-15649 SN - 0304-3800 VL - 452 CY - Elsevier ER - TY - JOUR A1 - Hornemann, Andrea A1 - Sinning, Denise A1 - Cortes, Sofia A1 - Campino, Lenea A1 - Emmer, Peggy A1 - Kuhls, Katrin A1 - Ulm, Gerhard A1 - Frohme, Marcus A1 - Beckhoff, Burkhard T1 - A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy JF - Analytical and Bioanalytical Chemistry N2 - Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens. KW - Fourier transform infrared spectroscopy KW - hierarchical cluster analysis (HCA) KW - principal components analysis (PCA) KW - Leishmania KW - DNA KW - multivariate differentiation Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-10080 SN - 1432-1130 ER -