Rapid and real-time identification of fungi up to species level with long amplicon nanopore sequencing from clinical samples

Abstract

The availability of long-read technologies, like Oxford Nanopore Technologies, provides the opportunity to sequence longer fragments of the fungal ribosomal operon, up to 6 Kb (18S-ITS1-5.8S-ITS2-28S) and to improve the taxonomy assignment of the communities up to species level and in real-time. We assess the applicability for taxonomic assignment of amplicons targeting a 3.5 Kb region (V3 18S-ITS1-5.8S-ITS2-28S D2) and a 6 Kb region (V1 18S-ITS1-5.8S-ITS2-28S D12) with the What’s in my pot (WIMP) classifier. We used the ZymoBIOMICSTM mock community and different microbiological fungal cultures as positive controls. Long amplicon sequencing correctly identified Saccharomyces cerevisiae and Cryptococcus neoformans from the mock community and Malassezia pachydermatis, Microsporum canis and Aspergillus fumigatus from the microbiological cultures. Besides, we identified Rhodotorula graminis in a culture mislabelled as Candida spp. We applied the same approach to external otitis in dogs. Malassezia was the dominant fungal genus in dogs’ ear skin, whereas Ma. pachydermatis was the main species in the healthy sample. Conversely, we identified a higher representation of Ma. globosa and Ma. sympodialis in otitis affected samples. We demonstrate the suitability of long ribosomal amplicons to characterize the fungal community of complex samples, either healthy or with clinical signs of infection.

The role of gut mycobiome in health and diseases

“…Long fragment could be reconstructed and identified as species precisely, decreasing the number of mislabeled species identified in illumine. 80 Secondarily, researches use Nanopore to detect fungi for the advantage of amplicon-based and PCR-free metagenomics technology. 77 …”

Long-Reads-Based Metagenomics in Clinical Diagnosis With a Special Focus on Fungal Infections

“…Metabarcoding of 1,312 clinical respiratory samples with the bacterial 16S gene and fungal ITS1/2 region identified pathogens in 51.5% of samples with a turnaround time of <24 h. Nanopore sequence alone identified 31% of samples, while 0.5% were identified with culture-based techniques only ( Wang et al, 2020 ). Long amplicon nanopore sequencing of the full ITS region and the whole fungal operon successfully identified all members of a mock community and microbial cultures ( D’Andreano et al, 2021 ). The full ITS region was also used to characterize the fungal microbiota of healthy and potentially infected clinical canine samples ( D’Andreano et al, 2021 ).…”

“…Long amplicon nanopore sequencing of the full ITS region and the whole fungal operon successfully identified all members of a mock community and microbial cultures ( D’Andreano et al, 2021 ). The full ITS region was also used to characterize the fungal microbiota of healthy and potentially infected clinical canine samples ( D’Andreano et al, 2021 ). The fungal intergenic spacer region has also been demonstrated to identify members from the Cryptococcus gattii and Cryptococcus neoformans species complexes by multiplexing 24 strains on a single MinION flow cell.…”

Nanopore-Based Surveillance of Zoonotic Bacterial Pathogens in Farm-Dwelling Peridomestic Rodents

“…With respect to metabarcoding, the ONT MinION platform has been successfully applied in several studies, including the characterization of bacterial mock communities [25,27,28]; microbiota profiling of species and tissues such as dog skin [29], canine feces [30], equine gut [31], water buffalo milk [32], sea louse [33], and microalgae [34]; identification of fungi [35]; and characterization of plastic-associated species in the Mediterranean sea [36]. Additionally, metagenetic analyses of environmental samples obtained from glacial regions [37], aquatic environments (e.g., ocean water column [38], river water [39], wastewater [40], and freshwater [41]), building dust [22], and the International Space Station [42] demonstrate the potential and applicability of nanopore sequencing for microorganism detection across diverse environments and field settings.…”