| Literature DB >> 29522426 |
Raphaël Enaud1,2,3, Louise-Eva Vandenborght4,5,6, Noémie Coron7,8,9, Thomas Bazin10,11, Renaud Prevel12, Thierry Schaeverbeke13,14, Patrick Berger15,16,17, Michael Fayon18,19,20, Thierry Lamireau21,22, Laurence Delhaes23,24,25.
Abstract
In recent years, the gut microbiota has been considered as a full-fledged actor of the gut-brain axis, making it possible to take a new step in understanding the pathophysiology of both neurological and psychiatric diseases. However, most of the studies have been devoted to gut bacterial microbiota, forgetting the non-negligible fungal flora. In this review, we expose how the role of the fungal component in the microbiota-gut-brain axis is legitimate, through its interactions with both the host, especially with the immune system, and the gut bacteria. We also discuss published data that already attest to a role of the mycobiome in the microbiota-gut-brain axis, and the impact of fungi on clinical and therapeutic research.Entities:
Keywords: brain–gut axis; dysbiosis; fungus; microbiome; mycobiome; neurological disorders; psychiatric disorders
Year: 2018 PMID: 29522426 PMCID: PMC5874636 DOI: 10.3390/microorganisms6010022
Source DB: PubMed Journal: Microorganisms ISSN: 2076-2607
Current metagenomic steps to analyze the mycobiome.
| Metagenomic Steps | Comments | References |
|---|---|---|
| Extraction of fungal communities |
Fungus cell wall is difficult to lyse: mechanical cell disruption (bead beating) or enzymatic cell lysis (lyticase) are usually used; currently, there is no consensus adopted for mycobiome analysis. Commercial kits are rarely optimized for fungal extraction | [ |
| Libraries preparation |
Metagenomic target debate: Either internal transcribed spacer (ITS1, ITS2) or 18S rDNA are used in mycobiome analysis. In the same study [ Specific NGS method is able to distinguish living and dead cells using pre-treatment with propidium monoazide (PMA) | [ |
| High-throughput sequencing |
Usual sequencing platforms: Illumina (Miseq), Ion Torrent (PGM)) Uneven ITS length among fungal species may impact species abundance in case of targeted amplicon sequencing Whole genome sequencing (shotgun metagenomic) may offer both accurate taxonomic assignments and functional data at gene levels but requires higher cost and intensive bioinformatic analysis | [ |
| Bioinformatics analysis |
Preprocessing, OTU picking, and taxonomic classification: lack of standardization even if QIIME (Quantitative Insights Into Microbial Ecology), an open-source bioinformatic pipeline, is one of the most used Quality and completeness of fungal databases lead to different proportions of unassigned sequences (17% of the total OTUs in some studies [ Improving taxonomic assignment quality requires an up-dated fungal database (current databases: Unite, Findley, RTL, TH) | [ |
Figure 1Proposed mechanisms of communication between the gut mycobiome and GBA. Figure inspired from [38,95]; for details about fungi–immune system interactions see review [49,96]. Abbreviations: CNS: central nervous system, GBA: gut–brain axis, HPAA: hypothalamic–pituitary–adrenal axis, IL: interleukin, SCFA: short chain fatty acid, TLR: Toll-like receptor.