DNA barcoding of human pathogenic fungi (#100)
With the constant increase in invasive fungal infections, the insufficiency of the current identification techniques (morphology/physiology), the limited available therapies and the emergence of resistant fungal strains there is an urgent need to improve fungal identification to enable a substantial improvement in clincial diseases outcome. Molecular based identification allows for an early identifictation of the fungal disease agent directly form clinical specimens or pure culture. The Internal Transcribed Spacer (ITS) regions have been used extensivelly in medical mycology for fungal ID. However, there are no ITS sequences of human pathogenic fungi deposited at BOLD. In 2010 a new ISHAM working goup was established, (1) to stet up a medical barcode database as part of BOLD by incorporating the different existing fungal group specific databases, (2) to extend the number of quality controlled ITS sequences to cover all medical important fungi, and (3) to achieve a special status as quality controlled reference sequences for those sequences within Ganbank. Currently sequence based ID is based on a cut-off of 98-99% similarity with the type culture of the species in question. Population based studies have shown that the sequence variation in clinical samples is much higher. Fungi have species dependent variable rates of polymorphisms in their ITS1/2 regions. Intra-species variation varies from 0-8.35% (C. parapsilosis 0% and C. tropicalis having 8.35%). Our findings lead to a redefinition of the recommended cut off values to 92% sequence similarity for the ITS1/2 region depending on the fungal species under investigation. As a result of a global collaboration the quality-controlled sequences of more then 2000 fungal strains are now available at www.mycologylab.org. The identified variation raises the question if the ITS region is the most appropriate locus for fungal barcoding. Whole genome sequence comparisions are currently underway to find either alternative genetic loci, better reflecting phylogenetic relationships amoung fungi, enabling a higher discrimination between fungal species and resulting in a more accurate ID.