|||Main Research Theme: Functional Microbial Bioinformatics|
Group Leader: Dr Heinrich Volschenk
NRF Rating: C
Office: JC Smuts Building A323
Phone: +27 21 808 5851
Fax:+27 21 808 5846
High-throughput technologies are generating vast amounts of multi-dimensional biological data on the genomics, proteomics and metabolomics fronts. There is an ever-growing need for the functional analysis and integration of these complex datasets to refine our interpretation of complex biological systems and redefine our understanding of the dynamic relationship between an organism’s physiology (phenome) and its genomic make-up, responsive transcriptome and expressed proteome.
In our lab, we employ functional bioinformatics approaches to study yeast physiology. This involves comparative molecular profiling of yeast genome sequences and/or transcriptome/proteome profiles, combined with pattern detection and network analyses to generate a molecular portrait of specific physiological responses in yeast. We currently employ high-throughput technologies such whole-genome next generation sequencing and LC-MS/MS-based proteomics, to generate comparative genome-wide QTL/SNP and proteome datasets, respectively. These molecular profiles are computationally analysed, by integrating data on the behaviour and interaction of thousands of genes and/or proteins, for their correlation and functional relationships related to specific physiological traits.
The comprehensive new insight of yeast physiology will in future be applied to:
(a) reverse engineering of industry-specific tailored yeast strains using a true systems biological approach
(b) discover unchartered paths to antifungal drug target discovery
(c) new function prediction of (un)characterized yeast genes/proteins
Polygenic phenotype analysis of S. cerevisiae for improved inhibitor tolerance
|Tolerance to fermentation inhibitors in lignocellulosic hydrolysate varies between S. cerevisiae strains and is generally regarded as polygenic traits, consisting of many gene variants that collectively contribute to the phenotype. Mass identification of gene variants using comparative whole-genome sequencing, with a technique known as pooled-segregant whole genome sequencing, combined with comparative proteomics analysis of yeast strains with superior inhibitor tolerance against strains that lacks this trait, will enable the simultaneous mapping of multiple genetic loci responsible for determining the complex traits of high inhibitor tolerance. Combining the genome-based bioinformatics approach above with shotgun proteomics will further illuminate through functional network analysis the target genes and proteins in the yeast governing these complex traits. The knowledge generated will inform future metabolic engineering strategies for S. cerevisiae to generate superior yeast strains better equipped for industrial-scale bioethanol production.|
|Advancing the field of natural product research: a case study investigating the physiological responses of human pathogenic fungi to antifungal medicinal South African plant extracts||Invasive mycoses are the major cause of death in immunocompromised humans. In sub-Saharan Africa, fluconazole is predominantly used as antifungal treatment, however long-term use of fluconazole and other antifungal agents has led to the emergence of resistance with no new classes of antifungal drug alternatives developed in the last 25 years. Furthermore, the dismal success of high-throughput approaches based on screening synthetic compound libraries has rekindled interest in medicinal plants as possible sources of novel antimicrobial compounds. Despite a significant body of research reporting on the antibiotic activity of plant extracts, the field still lacks scientific credibility, with the majority of studies limited to screening against target pathogens and basic active fraction analysis. Also, it has been suggested that screening hits don’t progress to drug development as a result of their toxicity to end-users. Verifiable knowledge about the mode of action and synergistic interactions between different compounds, as opposed to single highly active compounds, holds the promise to elevate medicinal plant research to a drug discovery platform with significant benefits to the fight against life-threatening human mycoses. This study aims to screen and identify medicinal plants from South Africa’s rich endemic plant biodiversity that exhibit antifungal activity against Cryptococcus neoformans and Candida albicans and display limited toxicity to human cells. Using this foundation, the study further aims to elucidate the antifungal mechanisms of active plant extracts by firstly employing a bioassay-guided, purification-independent detection of bioactive compound fingerprints with chemometric-assisted data analysis. Secondly, the study aims to elucidate the physiological stress response in the fungi and potentially identify novel fungal cellular targets relevant to the development of drug treatments using a comparative proteomics approach.|