A software pipeline for processing and identification of fungal ITS sequences

<p>Abstract</p> <p>Background</p> <p>Fungi from environmental samples are typically identified to species level through DNA sequencing of the nuclear ribosomal internal transcribed spacer (<it>ITS</it>) region for use in BLAST-based similarity searches in the International Nucleotide Sequence Databases. These searches are time-consuming and regularly require a significant amount of manual intervention and complementary analyses. We here present software – in the form of an identification pipeline for large sets of fungal <it>ITS </it>sequences – developed to automate the BLAST process and several additional analysis steps. The performance of the pipeline was evaluated on a dataset of 350 <it>ITS </it>sequences from fungi growing as epiphytes on building material.</p> <p>Results</p> <p>The pipeline was written in Perl and uses a local installation of NCBI-BLAST for the similarity searches of the query sequences. The variable subregion <it>ITS2 </it>of the <it>ITS </it>region is extracted from the sequences and used for additional searches of higher sensitivity. Multiple alignments of each query sequence and its closest matches are computed, and query sequences sharing at least 50% of their best matches are clustered to facilitate the evaluation of hypothetically conspecific groups. The pipeline proved to speed up the processing, as well as enhance the resolution, of the evaluation dataset considerably, and the fungi were found to belong chiefly to the <it>Ascomycota</it>, with <it>Penicillium </it>and <it>Aspergillus </it>as the two most common genera. The <it>ITS2 </it>was found to indicate a different taxonomic affiliation than did the complete <it>ITS </it>region for 10% of the query sequences, though this figure is likely to vary with the taxonomic scope of the query sequences.</p> <p>Conclusion</p> <p>The present software readily assigns large sets of fungal query sequences to their respective best matches in the international sequence databases and places them in a larger biological context. The output is highly structured to be easy to process, although it still needs to be inspected and possibly corrected for the impact of the incomplete and sometimes erroneously annotated fungal entries in these databases. The open source pipeline is available for UNIX-type platforms, and updated releases of the target database are made available biweekly. The pipeline is easily modified to operate on other molecular regions and organism groups.</p

Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Identification of Yeasts Is Contingent on Robust Reference Spectra

BACKGROUND: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for yeast identification is limited by the requirement for protein extraction and for robust reference spectra across yeast species in databases. We evaluated its ability to identify a range of yeasts in comparison with phenotypic methods. METHODS: MALDI-TOF MS was performed on 30 reference and 167 clinical isolates followed by prospective examination of 67 clinical strains in parallel with biochemical testing (total n = 264). Discordant/unreliable identifications were resolved by sequencing of the internal transcribed spacer region of the rRNA gene cluster. PRINCIPAL FINDINGS: Twenty (67%; 16 species), and 24 (80%) of 30 reference strains were identified to species, (spectral score ≥2.0) and genus (score ≥1.70)-level, respectively. Of clinical isolates, 140/167 (84%) strains were correctly identified with scores of ≥2.0 and 160/167 (96%) with scores of ≥1.70; amongst Candida spp. (n = 148), correct species assignment at scores of ≥2.0, and ≥1.70 was obtained for 86% and 96% isolates, respectively (vs. 76.4% by biochemical methods). Prospectively, species-level identification was achieved for 79% of isolates, whilst 91% and 94% of strains yielded scores of ≥1.90 and ≥1.70, respectively (100% isolates identified by biochemical methods). All test scores of 1.70-1.90 provided correct species assignment despite being identified to "genus-level". MALDI-TOF MS identified uncommon Candida spp., differentiated Candida parapsilosis from C. orthopsilosis and C. metapsilosis and distinguished between C. glabrata, C. nivariensis and C. bracarensis. Yeasts with scores of <1.70 were rare species such as C. nivariensis (3/10 strains) and C. bracarensis (n = 1) but included 4/12 Cryptococcus neoformans. There were no misidentifications. Four novel species-specific spectra were obtained. Protein extraction was essential for reliable results. CONCLUSIONS: MALDI-TOF MS enabled rapid, reliable identification of clinically-important yeasts. The addition of spectra to databases and reduction in identification scores required for species-level identification may improve its utility

A case of pulmonary cryptococcosis followed by pleuritis in an apparently immunocompetent patient during fluconazole treatment.

Cryptococcal pleuritis is rare in individuals with no underlying disease. We report a case of pulmonary cryptococcosis followed by pleuritis in a patient on fluconazole treatment. Biopsy of the pleura revealed a granuloma and a cryptococcal body, while PCR and sequence analysis of extracted DNA from the pleura proved the presence of Cryptococcus species, most likely C. neoformans. Voriconazole with flucytosine and drainage of the pleural effusion were effective in treating the patient