Designing genome-wide mutagenesis approaches for non-model organisms by leveraging an artificial transposon, deep sequencing, machine learning and a stable haploid isolate
The human pathogen Candida albicans was recently found to have a viable haploid state (Hickman et al. 2013). We used a stable haploid isolate as the basis for an in vivo transposon screen by exploiting the heterologous mini-AcDs transposon system (Weil and Kunze 2000). Together with high throughput TnSeq deep sequencing (van Opijnen, Bodi, and Camilli 2009) and analysis, we generated a large-scale pooled library of mutants carrying insertions that can be screened for many functions to identify the mutants that are enriched or depleted under a given condition.
We first used the collection to determine gene essentiality comprehensively across the complete C. albicans genome. We applied Random Forrest machine learning algorithms trained on sets of genes reported in the literature to be non-essential in C. albicans, together with C. albicans orthologs of genes essential in both Saccharomyces cerevisiae and Schizosaccharomyces pombe.
As expected, the essentiality of genes that are orthologous between C.albicans and/or S. cerevisiae and S.pombe is well conserved. We identified “core” essential genes necessary for viability in all three organisms. Outliers include genes duplicated in specific genomes and not in others. Furthermore, we found that some genes listed as essential can tolerate insertions outside of specific domains, highlighting the importance of specific domains in gene function and the ability of transposon mutagenesis to detect them. The identification of genes essential in fungi and not in humans also highlights potential targets for the development of new antifungal therapeutics.
In summary, in vivo transposon mutagenesis is a facile method for studying gene essentiality in non-model eukaryotic pathogens. This library has much potential to identify essential genes, and new genes or genomic regions involved in a broad range of measurable functions.