Nanopore Sequencing of the Fungal Intergenic Spacer Sequence as a Potential Rapid Diagnostic Assay

Abstract

Fungal infections are being caused by a broadening spectrum of fungi, yet in many cases, identification to the species level is required for proper antifungal selection. We investigated the fungal intergenic spacer sequence (IGS) in combination with nanopore sequencing, for fungal identification. We sequenced isolates from two Cryptococcus species complexes, C. gattii and C. neoformans, which are the main pathogenic members of this genus, using the Oxford Nanopore Technologies MinION device and Sanger sequencing. There is enough variation within the two complexes to argue for further resolution into separate species, which we wanted to see if nanopore sequencing could detect. Using the R9.4.1 flow cell, IGS sequence identities averaged 99.57% compared to Sanger sequences of the same region. When the newer R10.3 flow cell was used, accuracy increased to 99.83% identity compared to the same Sanger sequences. Nanopore sequencing errors were predominantly in regions of homopolymers, with G homopolymers displaying the largest number of errors and C homopolymers displaying the least. Phylogenetic analysis of the nanopore and Sanger derived sequences resulted in indistinguishable trees. Comparison of average percent identities between the C. gattii and C. neoformans species complexes resulted in only a 74-77% identity between the two complexes. Sequencing using the nanopore platform could be completed in less than an hour and samples could be multiplexed in groups as large as twenty-four sequences in a single run. These results suggest that sequencing the IGS region using nanopore sequencing could be a potential new molecular diagnostic strategy.

A method for determining the animals of origin in crude drugs using MinION, a compact next-generation sequencer

“…The accuracy of the R10.3 ow cell exceeded 99% (99.83%) for human leukocyte antigen (HLA) typing 16 , which was higher compared with Sanger sequencing for fungal identi cation. 17 Moreover, the maximum incorrect base calls in mixed bases was only 4% in the MinION consensus sequence in human mitochondrial DNA analysis. 18 Therefore, it was considered that threshold value in this study, 0.05, was suitable for distinguishing and identifying animals from a mixture sample.…”

A targeted approach with nanopore sequencing for the universal detection and identification of flaviviruses

“…However, the sequencing platform has received a major improvement in accuracy with the new R10.3 flowcell in pair with new basecalling tool (Bonito) 21 . The accuracy has been validated in several studies showing improvements in both consensus 22 and sequencing accuracy 23 , including sequencing accuracy for the homopolymer region 22 , 24 . With the improved accuracy, index sequences can be shortened to minimize dimer formation, which should improve PCR efficiency.…”

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

“…The introduction of new flow cells has led to strong improvements, with average accuracies of 87-98% being commonly reported (Loit et al, 2019;Logsdon et al, 2020). The highest accuracy ever reported after bioinformatics polishing, which might be computation-intensive and may take weeks, stands at >99% (Ashikawa et al, 2018;Morrison et al, 2020). In addition, new bioinformatic tools to improve the accuracy of nanopore reads are now readily available (Loman et al, 2015;Koren et al, 2017;Salmela et al, 2017;Xiao et al, 2017;Hu et al, 2021).…”

“…Sequencing errors in regions with homopolymers were observed. However, with the R10.3 flow cell, this error rate was reduced by 57% and the sequence identity increased to 99.83% ( Morrison et al, 2020 ).…”