Host-mycobiome metabolic interactions in health and disease

Abstract

Fungal communities (mycobiome) have an important role in sustaining the resilience of complex microbial communities and maintenance of homeostasis. The mycobiome remains relatively unexplored compared to the bacteriome despite increasing evidence highlighting their contribution to host-microbiome interactions in health and disease. Despite being a small proportion of the total species, fungi constitute a large proportion of the biomass within the human microbiome and thus serve as a potential target for metabolic reprogramming in pathogenesis and disease mechanism. Metabolites produced by fungi shape host niches, induce immune tolerance and changes in their levels prelude changes associated with metabolic diseases and cancer. Given the complexity of microbial interactions, studying the metabolic interplay of the mycobiome with both host and microbiome is a demanding but crucial task. However, genome-scale modelling and synthetic biology can provide an integrative platform that allows elucidation of the multifaceted interactions between mycobiome, microbiome and host. The inferences gained from understanding mycobiome interplay with other organisms can delineate the key role of the mycobiome in pathophysiology and reveal its role in human disease.

Keywords: Mycobiome; host-mycobiome interaction; metabolism; microbiome; secondary metabolism; systems biology.

Figure 1.

Fundamental metabolic interactions between host-mycobiome in health and disease. A. indicates Candida contribution to the production of γ-amino butyric acid (GABA) through the tricarboxylic acid cycle to produce succinate may perceptively occur during systemic infection. GABA has a role in dampening the effect of the nervous system, and generally, deficiency involves epilepsy. Indirectly targeting mycobiome in specific regions such as Candida species can have a better effect than providing analogues of GABA that has been identified to lead to anxiety, stress and seizures. Exploring this metabolic pathway of the mycobiome, especially targeting the succinate pathway, the production of semi-aldehydrase could lead to alteration of disease with better regulation from the microbiota, as alternatively, high levels of GABA have been linked to Alzheimer’s disease. B. Penicillium species’ ability to produce the mycotoxin called citrinin is toxic to cause renal nephrosis. Drugs have been developed to inhibit the effect of citrinin in hepatoma, and several animal studies have shown the benefit. Ostry et al., 2013 have highlighted the dangerous effect of citrinin in dietary sources. There has been no established link of mycobiome being the contributor of toxin in humans and whether diverting the polyketide pathway can reduce renal cell toxicity. C Aflatoxin is a common secondary metabolite of the Aspergillus family. It has been associated with cancer morbidity and inducing tumour suppressor gene p53. The potential effect of the presence of Aspergillus needs to be investigated and whether manipulating the metabolic pathway can give a better indicator of being able to reverse the effects of aflatoxin by reducing the levels of the malonyl-coA pathway. All these potential pathways give us a clear indication of how the study of the metabolism of the mycobiome is essential in understanding pathogenesis across a wide breadth of diseases.

Figure 2.

System and synthetic biology approach in investigating mycobiome’s important role in the gut-liver axis. This image shows the interaction of the microbiome-mycobiome with the host cells in the gut, translocation of intermediaries through the blood, and prospectively leading to the composition of the liver environment to change. The biological knowledge from the collection of omics data such as proteome, metabolome and transcriptome generates information that can be integrated into functional mathematical models. The structural data is placed into the stoichiometric matrix and after several steps of adding biochemical information the draft of the GSMM can be reconstructed and further validated for new biological interpretation and predictions. Different constraint can be applied on the GSMMs to investigate the models for novel discovery. CRISPR as one of the gene editing approaches in validating predictions based on GSMM; these can be done using the CRISPR-cas9 system to perform genome modification such as gene slicing, gene mutation, secondary metabolite modification, base editing, and gene editing tagging and gene overexpression, down-regulation methods. The application can be used in tackling drug resistance, alteration of the metabolic pathway with the possibility of amending toxic pathways in pathogenesis, rationalising gene essentiality and genome-wide screening. The application of these potential methods in assessing the mycobiome community and particularly within the gut-liver axis.