Computation-Driven Mechanistic Understanding of the Cellular Cost and Regulation of Melanin Production

Computation-Driven Mechanistic Understanding of the Cellular Cost and Regulation of Melanin Production

Wheaton Schroeder, Jyothi Kumar, Rajib Saha and Steve Harris

The University of Nebraska – Lincoln, Lincoln, NE

Exophiala dermatitidis, a melanized extremophilic black yeast, is of interest primarily for its ability to synthesize melanin as a stress protectant. In addition, as an emerging fungal pathogen, melanin deposition in the cell wall hides this organism from the host immune system, often leading to high mortality rates, and without which its pathogenic efficacy is significantly decreased. Thus, with a small genome E. dermatitidis may serve for dual purposes: first, as a model system for melanocytes to explore treatments for melanin-related human skin disorders such as albinism, and second, as a model pathogenic organism to study how to combat infections by disrupting melanin production, not only from E. dermatitidis, but also for other melaninized fungal pathogens such as Cryptococcus neoformans. At present, relatively little is known about the regulation and kinetics of melanin production in E. dermatitidis, and in particular whether synthesis of melanin imposes a severe metabolic cost on the fungus. Our chosen tool for filling this knowledge gap is computational modeling, which is a promising approach that has not yet been systematically applied to extremophilic fungi or to human fungal pathogens.

Computational modeling of metabolism is now an indispensable tool to drive the processes of understanding, discovering, and redesigning of biological systems. Although Flux Balance Analysis (FBA) is the primary tool used for this purpose, it has significant limitations due to the lack of reaction kinetics, chemical species concentration, and metabolic regulation. Hence, the development a kinetic model framework will allow for a greater understanding of E. dermatitidis as a pathogen and as a model organism.  At present, one of the greatest challenges to this approach is that this organism’s metabolism is not well studied. Specific challenges to overcome include that the genome is less than 50% annotated, there is no metabolic model available in either literature or in public databases such as ModelSeed, and there are no genes or genome entries for this organism in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Hence, the necessary first step in computational modeling is to build a genome-scale model by using the available annotations of E. dermatitidis, published models, and homology information of related species (such as Aspergillus-genus).

Once the genome-scale model is constructed, a novel approach to building a kinetic model framework using FBA, transcriptomic, metabolomics, experimental, and genomic data is used. The completed kinetic model framework currently has about 1700 reactions and 2100 metabolites. This modeling framework will next be used for exploring important questions of biosynthesis, regulation, and metabolic cost related to melanin production, as a freestanding organism, as a pathogenic organism, and as a model system for human melanocytes. In addition, the computational model will be useful for in silico discovery and exploration of possible treatment options for infections cause by E. dermatitidis and related species by inhibiting or downregulating melanin synthesis, presenting significant cost savings in developing viable treatment options. Further, this computational model can be used as an in silico model of human melanocytes, to study and hopefully suggest strategies to cure melanin-related skin disorders such as albinism.