DNA metabarcoding uncovers fungal diversity of mixed airborne samples in Italy

Banchi, Elisa; Ametrano, Claudio Gennaro; Stanković, D; Verardo, Pierluigi; Moretti, Olga; Gabrielli, F; Lazzarin, Stefania; Borney, Maria Francesca; Tassan, Francesca; Tretiach, Mauro; Pallavicini, Alberto

doi:10.1371/journal.pone.0194489

Cited by 63 publications

(62 citation statements)

References 109 publications

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“…Taxonomic classification at species and strain levels using metabarcoding and metagenomic data has been considered inaccurate (Nilsson et al 2019;Sczyrba et al 2017;Yamamoto et al 2014), raising the question of how our metatranscriptomics approach succeeded in identifying closely-related fungal strains. Metabarcoding relies on a single or multiple genetic marker(s) (Banchi et al 2018;e.g. McGuire et al 2013;Schmidt et al 2013), which does not contain sufficient phylogenetic information to differentiate some closely related fungal lineages (Balasundaram et al 2015;Nilsson et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions

et al. 2019

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High-throughput sequencing (HTS) enables the generation of large amounts of genome sequence data at a reasonable cost. Organisms in mixed microbial communities can now be sequenced and identified in a culture-independent way, usually using amplicon sequencing of a DNA barcode. Bulk RNA-seq (metatranscriptomics) has several advantages over DNA-based amplicon sequencing: it is less susceptible to amplification biases, it captures only living organisms, and it enables a larger set of genes to be used for taxonomic identification. Using a model mock community comprising 17 fungal isolates, we evaluated whether metatranscriptomics can accurately identify fungal species and subspecies in mixed communities. Overall, 72.9% of the RNA transcripts were classified, from which the vast majority (99.5%) were correctly identified at the species level. Of the 15 species sequenced, 13 were retrieved and identified correctly. We also detected strain-level variation within the Cryptococcus species complexes: 99.3% of transcripts assigned to Cryptococcus were classified as one of the four strains used in the mock community. Laboratory contaminants and/or misclassifications were diverse, but represented only 0.44% of the transcripts. Hence, these results show that it is possible to obtain accurate species-and strain-level fungal identification from metatranscriptome data as long as taxa identified at low abundance are discarded to avoid false-positives derived from contamination or misclassifications. This study highlights both the advantages and current challenges in the application of metatranscriptomics in clinical mycology and ecological studies.

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Section: Discussionmentioning

confidence: 99%

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions

et al. 2019

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“…Taxonomic classification at species and strain levels using metabarcoding and metagenomic data has been considered inaccurate (Nilsson et al 2019; Sczyrba et al 2017; Yamamoto et al 2014), raising the question of how our metatranscriptomics approach succeeded in identifying closely-related fungal strains. Metabarcoding relies on a single marker gene (Banchi et al 2018; e.g. McGuire et al 2013; Schmidt et al 2013), which does not contain sufficient phylogenetic information to differentiate some closely related fungal lineages (Balasundaram et al 2015; Nilsson et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities

Marcelino

Irinyi

Eden

et al. 2019

Preprint

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21High-throughput sequencing (HTS) enables the generation of large amounts of genome 22 sequence data at a reasonable cost. Organisms in mixed microbial communities can now 23 be sequenced and identified in a culture-independent way, usually using amplicon 24 sequencing of a DNA barcode. Bulk RNA-seq (metatranscriptomics) has several 25 advantages over DNA-based amplicon sequencing: it is less susceptible to amplification 26 biases, it captures only living organisms, and it enables a larger set of genes to be used for 27 taxonomic identification. Using a defined mock community comprised of 17 fungal isolates, 28 we evaluated whether metatranscriptomics can accurately identify fungal species and 29 subspecies in mixed communities. Overall, 72.9% of the RNA transcripts were classified, 30 from which the vast majority (99.5%) were correctly identified at the species-level. Of the 15 31 species sequenced, 13 were retrieved and identified correctly. We also detected strain-level 32 variation within the Cryptococcus species complexes: 99.3% of transcripts assigned to 33 Cryptococcus were classified as one of the four strains used in the mock community. 34 Laboratory contaminants and/or misclassifications were diverse but represented only 35 0.44% of the transcripts. Hence, these results show that it is possible to obtain accurate 36 species-and strain-level fungal identification from metatranscriptome data as long as taxa 37 identified at low abundance are discarded to avoid false-positives derived from 38 contamination or misclassifications. This study therefore establishes a base-line for the 39 application of metatranscriptomics in clinical mycology and ecological studies. 40

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“…Blaalid et al [24] obtained similar results when using either ITS1 or ITS2 to perform fungal metabarcoding with environmental data, but Banchi et al [25] showed discrepancies and biases in the detection of Basidiomycota when ITS1 or ITS2 were used as metabarcode for lichen mycobiomes, and suggested the complementary analysis of both ITS1 and ITS2 to reliably estimate the taxonomic diversity of the samples. In similar studies, Wang et al [26] concluded conversely that ITS1 provides a better DNA barcode than ITS2 allowing a better species discrimination efficiency, whereas the ITS2 has been specifically selected and preferred to ITS1 in another study to catch fungal diversity in airborne samples [27]. It is clear that an a priori choice of the region/s to target was not ideal, and for this reason, our analysis of the fungal communities targeted specifically both the ITS1 and the ITS2 regions.…”

Section: Introductionmentioning

confidence: 94%

Soil Fungal Communities Investigated by Metabarcoding within Simulated Forensic Burial Contexts

Procopio

Ghignone

Voyron

et al. 2020

Preprint

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Background One of the most debated questions in forensic science is the estimation of the post-mortem interval (PMI). Despite the large amount of research currently performed to improve the PMI estimation, there is still the need for additional improvements, particularly in cases of severely decomposed buried remains. A novel alternative to the morphological examination of the remains is the analysis of the soil microbial communities. Bacteria and fungi are ubiquitous and can be found in the soil and in/on the corpses, and their shifts in populational compositions present at different PMIs may reveal insights for PMI estimation. Despite it already having been revealed that bacteria might be good candidates for this type of analysis, there are knowledge gaps for this type of application when dealing with fungal communities. For this reason, we performed the metabarcoding analysis of the mycobiome present in the soil after prolonged decomposition times, from one- to six-months, targeting both the Internal Transcribed Spacer (ITS) 1 and 2, to elucidate which of the two was more suitable for this purpose. Results Our results showed a decrease in the fungal taxonomic richness associated with increasing PMIs and the presence of specific trends associated with specific PMIs, such as the increase of the Mortierellomycota taxa after four- and six-months post-mortem and of Ascomycota particularly after two months, and the decrease of Basidiomycota from the first to the last time point. We have found a limited amount of taxa specifically associated with the presence of the mammalian carcasses and not present in the control soil, showing that the overall the taxa which are contributing the most to the changes in the community originate from the soil and are not introduced by the carrion, extending the potential to perform comparisons with other experimental studies with different carrion species. Conclusions This study has been the first one conducted on gravesoil, and sets the baseline for additional studies, showing the potential to use fungal biomarkers in combination with bacterial ones to improve the accuracy of the PMI predictive model based on the shifts in the soil microbial communities.

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DNA metabarcoding uncovers fungal diversity of mixed airborne samples in Italy

Cited by 63 publications

References 109 publications

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities

Soil Fungal Communities Investigated by Metabarcoding within Simulated Forensic Burial Contexts

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