title: Multi-omics approaches to understanding Candida biofilms
Creators: name: Delaney, Christopher Daniel
Publisher: name: University of Glasgow
Year: 2021

description: Candida biofilms are a substantial clinical and human health burden which are still underappreciated. Benefits afforded by morphogenic switching from planktonic to biofilm communities include resistance to antimicrobials in the host’s immune system, and resilience to mechanical disruption, all of which complicate the treatment and management of infections. Biofilm formation in Candida spp. is influenced by numerous factors, including response to the host, pH, bacteria, and many other environmental factors. This is further complicated by inherent heterogeneity within candidal populations in respect to biofilm forming capabilities and its response to external stimuli. Biofilms are heterogeneous by their nature, formed of populations of yeast and hyphal cells in a consortium of morphological states. Many variables exist to influence biofilm heterogeneity in Candida spp. and can influence the clinical outcomes and observations. The overarching aim of this thesis was to explore factors that influences C. albicans biofilm formation using omics-based approaches. We performed analysis on the microbiome derived from three distinct oral niches in denture stomatitis patients. Alpha and beta diversity measures were extrapolated and compared to identify perturbations in the microbiome that were related to either the oral hygiene or the Candida burdenof the individuals. Correlation analysis between phyla, oral hygiene and fungal load were performed to identify significant relationships. Secondly, we selected clinical isolates, from our Scottish candidaemia study cohort, which were deemed high and low biofilm isolates as determined by biomass assays. We assessed the biofilm forming capabilities in media supplemented with and without serum. These assays consisted of crystal violet biomass assay and measurements ofhyphal. We also utilised SEM to visualise the phenotypes of the high and low isolates with and without serum. HBF and LBF isolates were then grown at 90min, 4h and 24h in the presence and absence of serum before being submitted to RNASequencing by Illumina. Differential expression analysis was performed using DESeq2 before over representation and gene set enrichment analysis. Cell wall proteomics on high and low isolates was also performed to identify computational changes in the cell wall. Thirdly, we performed metabolomic analysis both targeted and untargeted on the supernatants of HBF and LBF grown in the presence or absence of serum for 4 and 24h. Features were identified from the LC-MS peaks by PiMP and analysis of differentially abundant analytes between our isolates and growth conditions were performed. Functional analysis of the annotated analytes was then performed by pathway activity profiling. Finally, utilising our identified differentially expressed features from metabolomic and transcriptomic analysis we submitted both datasets to integrative analysis. Using a combination of conceptual, joint pathway analysis by MetaboAnalyst and multivariate Analysis using the MixOmics data integration package. From our microbiome analysis we observed that the oral hygiene measures had no significant effect on the diversity or composition of the oral microbiome. Candida similarly had no impact on the alpha diversity of the oral microbiome. However, we did observe some relationship in the beta diversity which correlated with Candida load. Further investigation identified correlations of genus including Lactobacillus with Candida load. From our high and low Candida candidaemia isolates we observed phenotypic switching of LBF in the presence of serum. We also found functional differences related to this phenotypic switching. The low biofilm response to serum included enrichment in fatty acid and aycl-coA metabolic pathways. Metabolomic analysis revealed changes in arachidonic acid metabolism in serum grown isolates and changes in the amino acid metabolism between LBF and HBF isolates. Integrating these data, we were able to observe overlaps in the metabolic reprogramming of C. albicans isolates in serum with joint pathway analysis confirming changes in the fatty acid metabolic response in both transcriptomic and metabolomic data. Multivariate analysis by sPLS-DA identified several highly covariate discriminatory features with and without the presence of serum. These included many genes of currently unknown function and a downregulation of specific genes in serum including zinc transport. Through the application of transcriptomics and metabolomics we have demonstrated that these holistic methodologies are invaluable to biofilm research. We identified Molecular processes and metabolomic reprogramming of C. albicans in response to the biofilm inducing stimulus of serum. We also highlight the current and potential benefits that integration of multiple omics data sets provides. Integration is not without its challenges, however, and we identify some key methodologies that could improve interpretability of omics datasets derived from microbial communities. As Candida spp. do not exist within a vacuum, and infectious disease aetiology is dependent on the interactions between fungal and bacterial species, understanding the mechanisms that govern these biofilm models will help us to identify important factors and potential therapeutic strategies.