1887

Abstract

Although fungi are fundamental to the human microbiome, the diversity and dynamics of the mycobiome is poorly understood, particularly in considering their association with infectious disease, autoimmune disorders and atopy that affect immunocompromised individuals and infants. Characterising the human mycobiome faces several challenges relating to their low abundance and lack of standardized procedures for sample collection and isolation of viable cells and/or quality genetic material for culture-dependent and independent taxonomic and functional characterisation. To address these issues, we have developed a mycobiome analysis pipeline employing both culture-dependent and independent methods to identify as well as isolate, where possible, the fungal taxa populating the human intestinal tract. In a proof-of-concept study this pipeline has been used to identify fungal populations in faecal samples obtained from a small cohort of young infants, aged 2 years or younger. All were born prematurely, and severely immunocompromised and at risk from invasive and potentially lethal microbial infections, including those caused by fungal overgrowth. We have used this combined approach successfully to identify the fungi present in each individual infant, and to recover viable isolates. To date, Candida albicans and C. parapsilosis are the most frequently isolated fungi. While both are major opportunistic human fungal pathogens, C. parapsilosis is particularly problematic to preterm babies, due to its innate ability to form biofilms. Detailed characterisation of these isolates is currently underway. Two large-scale longitudinal microbiome studies have started at the Quadram Institute, and our validated analysis pipeline will be incorporated to define the fungal component of each study participant.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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/content/journal/acmi/10.1099/acmi.ac2019.po0148
2019-04-08
2024-03-29
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http://instance.metastore.ingenta.com/content/journal/acmi/10.1099/acmi.ac2019.po0148
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