1. DNA metabarcoding uncovers fungal diversity of mixed airborne samples in ItalyElisa Banchi, Claudio Gennaro Ametrano, David Stanković, Pierluigi Verardo, Olga Moretti, Francesca Gabrielli, Stefania Lazzarin, Maria Francesca Borney, Francesca Tassan, Mauro Tretiach, Alberto Pallavicini, Lucia Muggia, 2018, original scientific article Abstract: Fungal spores and mycelium fragments are particles which become and remain airborne and have been subjects of aerobiological studies. The presence and the abundance of taxa in aerobiological samples can be very variable and impaired by changeable climatic conditions. Because many fungi produce mycotoxins and both their mycelium fragments and spores are potential allergens, monitoring the presence of these taxa is of key importance. So far data on exposure and sensitization to fungal allergens are mainly based on the assessment of few, easily identifiable taxa and focused only on certain environments. The microscopic method used to analyze aerobiological samples and the inconspicuous fungal characters do not allow a in depth taxonomical identification. Here, we present a first assessment of fungal diversity from airborne samples using a DNA metabarcoding analysis. The nuclear ITS2 region was selected as barcode to catch fungal diversity in mixed airborne samples gathered during two weeks in four sites of North-Eastern and Central Italy. We assessed the taxonomic composition and diversity within and among the sampled sites and compared the molecular data with those obtained by traditional microscopy. The molecular analyses provide a tenfold more comprehensive determination of the taxa than the traditional morphological inspections. Our results prove that the metabarcoding analysis is a promising approach to increases quality and sensitivity of the aerobiological monitoring. The laboratory and bioinformatic workflow implemented here is now suitable for routine, high-throughput, regional analyses of airborne fungi. Keywords: fungi, fungal spores, taxonomy, sequence databases Published in DiRROS: 24.07.2024; Views: 339; Downloads: 142
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2. PLANiTS : a curated sequence reference dataset for plant ITS DNA metabarcodingElisa Banchi, Claudio Gennaro Ametrano, Samuele Greco, David Stanković, Lucia Muggia, Alberto Pallavicini, 2020, original scientific article Abstract: DNA metabarcoding combines DNA barcoding with high-throughput sequencing to identify different taxa within environmental communities. The ITS has already been proposed and widely used as universal barcode marker for plants, but a comprehensive, updated and accurate reference dataset of plant ITS sequences has not been available so far. Here, we constructed reference datasets of Viridiplantae ITS1, ITS2 and entire ITS sequences including both Chlorophyta and Streptophyta. The sequences were retrieved from NCBI, and the ITS region was extracted. The sequences underwent identity check to remove misidentified records and were clustered at 99% identity to reduce redundancy and computational effort. For this step, we developed a script called ‘better clustering for QIIME’ (bc4q) to ensure that the representative sequences are chosen according to the composition of the cluster at a different taxonomic level. The three datasets obtained with the bc4q script are PLANiTS1 (100 224 sequences), PLANiTS2 (96 771 sequences) and PLANiTS (97 550 sequences), and all are pre-formatted for QIIME, being this the most used bioinformatic pipeline for metabarcoding analysis. Being curated and updated reference databases, PLANiTS1, PLANiTS2 and PLANiTS are proposed as a reliable, pivotal first step for a general standardization of plant DNA metabarcoding studies. The bc4q script is presented as a new tool useful in each research dealing with sequences clustering. Keywords: DNA metabarcoding, reference datasets Published in DiRROS: 19.07.2024; Views: 222; Downloads: 127
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3. Differences in reporting the ragweed pollen season using Google Trends across 15 countriesJean Bousquet, Ioana Agache, Uwe Berger, Karl-Christian Bergmann, Jean-Pierre Besancenot, Philippe J. Bousquet, Thomas Casale, Gennaro d'Amato, Igor Kaidashev, Musa Khaitov, Ralph Mösges, Kristof Nekam, Gabrielle L. Onorato, Davor Plavec, Aziz Sheikh, Michel Thibaudon, Robert Vautard, Mihaela Zidarn, 2018, review article Abstract: Background: Google Trends (GT) searches trends of specific queries in Google, which potentially reflect the real-life epidemiology of allergic rhinitis. We compared GT terms related to ragweed pollen allergy in American and European Union countries with a known ragweed pollen season. Our aim was to assess seasonality and the terms needed to perform the GT searches and to compare these during the spring and summer pollen seasons. Methods: We examined GT queries from January 1, 2011, to January 4, 2017. We included 15 countries with a known ragweed pollen season and used the standard 5-year GT graphs. We used the GT translation for all countries and the untranslated native terms for each country. Results: The results of "pollen," "ragweed," and "allergy" searches differed between countries, but "ragweed" was clearly identified in 12 of the 15 countries. There was considerable heterogeneity of findings when the GT translation was used. For Croatia, Hungary, Romania, Serbia, and Slovenia, the GT translation was inappropriate. The country patterns of "pollen," "hay fever," and "allergy" differed in 8 of the 11 countries with identified "ragweed" queries during the spring and the summer, indicating that the perception of tree and grass pollen allergy differs from that of ragweed pollen. Conclusions: To investigate ragweed pollen allergy using GT, the term "ragweed" as a plant is required and the translation of "ragweed" in the native language needed. Keywords: allergy and immunology, allergens, seasonal allergic rhinitis, rhinitis, pollen, ambrosia, Google Trends, hay fever Published in DiRROS: 20.11.2020; Views: 1452; Downloads: 335
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