Fungals are opportunistic pathogens that can cause invasive infections primarily among immunocompromised individuals. Traditionally, fungi have been identified by culturing on agar plates and using morphological criteria. Molecular detection methods such as polymerase chain reaction (PCR) and sequencing is faster and superior at identifying fungi at species level compared to culturing and microscopic examination. The aim of this project was to identify fungi at the species level by sequencing the internal transcribed spacer (ITS) region of different control strains and patient samples. This was accomplished using a nested PCR followed by Nanopore sequencing. Two different workflows using different databases were created. One workflow created a consensus sequence which was followed by a BLAST search. The other workflow used an Emu program and mapped reads against the UNITE database. The result was compared to identification previously achieved. Amplification was successful in 28 out of 30 positive samples. The BLAST workflow managed to identify nine out of eleven samples, but was difficult to interpret. The Emu workflow was only concordant with previous identification in 20 out of 28 species in sequenced samples and failed to identify 4 previously identified fungi at the species level, but was easier to interpret and could identify several species from a mixed culture. Amplifying and sequencing of the ITS region can in several cases provide accurate identification, but the method of extraction, choice of DNA polymerase and choice of database need to be considered for successful amplification and accurate species identification before implementation as a diagnostic method.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-530695 |
Date | January 2024 |
Creators | Billström, Madelene |
Publisher | Uppsala universitet, Institutionen för medicinsk cellbiologi |
Source Sets | DiVA Archive at Upsalla University |
Language | Swedish |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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