Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions
Abstract 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...
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BMC
2019-08-01
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| Series: | IMA Fungus |
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| Online Access: | http://link.springer.com/article/10.1186/s43008-019-0012-8 |
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| author | Vanesa R. Marcelino Laszlo Irinyi John-Sebastian Eden Wieland Meyer Edward C. Holmes Tania C. Sorrell |
| author_facet | Vanesa R. Marcelino Laszlo Irinyi John-Sebastian Eden Wieland Meyer Edward C. Holmes Tania C. Sorrell |
| author_sort | Vanesa R. Marcelino |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-f14bb0ada44945b297b68030dba0558f |
| institution | Kabale University |
| issn | 2210-6359 |
| language | English |
| publishDate | 2019-08-01 |
| publisher | BMC |
| record_format | Article |
| series | IMA Fungus |
| spelling | doaj-art-f14bb0ada44945b297b68030dba0558f2025-02-02T13:43:43ZengBMCIMA Fungus2210-63592019-08-0110111010.1186/s43008-019-0012-8Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditionsVanesa R. Marcelino0Laszlo Irinyi1John-Sebastian Eden2Wieland Meyer3Edward C. Holmes4Tania C. Sorrell5Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of SydneyMarie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of SydneyMarie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of SydneyMarie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of SydneyMarie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of SydneyMarie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of SydneyAbstract 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.http://link.springer.com/article/10.1186/s43008-019-0012-8FungiMeta-transcriptomicsMetagenomicsMicrobiome |
| spellingShingle | Vanesa R. Marcelino Laszlo Irinyi John-Sebastian Eden Wieland Meyer Edward C. Holmes Tania C. Sorrell Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions IMA Fungus Fungi Meta-transcriptomics Metagenomics Microbiome |
| title | Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions |
| title_full | Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions |
| title_fullStr | Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions |
| title_full_unstemmed | Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions |
| title_short | Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – a proof of concept under laboratory conditions |
| title_sort | metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities a proof of concept under laboratory conditions |
| topic | Fungi Meta-transcriptomics Metagenomics Microbiome |
| url | http://link.springer.com/article/10.1186/s43008-019-0012-8 |
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