Population perspectives on functional genomic variation in yeast

Use of the Iron-Responsive RBT5 Promoter for Regulated Expression in Candida albicans

Engineered conditional gene expression is used in appraisal of gene function and pathway relationships. For pathogens like the fungus Candida albicans, conditional expression systems are most useful if they are active in the infection environment and if they can be utilized in multiple clinical isolates. Here, we describe such a system. It employs the RBT5 promoter and can be implemented with a few PCRs. We validated the system with RBT5 promoter fusions to two genes that promote filamentation and polarized growth, UME6 and HGC1, and with efg1Δ/Δ mutants, which are defective in an activator of filamentous growth. An RBT5 promoter fusion to either gene enabled filamentous growth of an efg1Δ/Δ mutant of strain SC5314 in iron-limited media, including RPMI with serum and yeast extract-peptone-dextrose with bathophenanthrolinedisulfonic acid. The RBT5-UME6 fusion promoted filamentation of efg1Δ/Δ mutants in RPMI with serum of four other clinical C. albicans isolates as well. In a mouse model of disseminated candidiasis, the RBT5-UME6 fusion promoted filamentation of the SC5314 efg1Δ/Δ mutant in kidney tissue, an indication that the RBT5 promoter is active in the iron-limited host environment. The RBT5 promoter expands the conditional expression toolkit for C. albicans genetics. IMPORTANCE Genetic strategies have been vital for mechanistic analysis of biological processes. Here, we describe a genetic tool for the fungal pathogen Candida albicans.

Massive QTL analysis identifies pleiotropic genetic determinants for stress resistance, aroma formation, and ethanol, glycerol and isobutanol production in Saccharomyces cerevisiae

BACKGROUND

The brewer's yeast Saccharomyces cerevisiae is exploited in several industrial processes, ranging from food and beverage fermentation to the production of biofuels, pharmaceuticals and complex chemicals. The large genetic and phenotypic diversity within this species offers a formidable natural resource to obtain superior strains, hybrids, and variants. However, most industrially relevant traits in S. cerevisiae strains are controlled by multiple genetic loci. Over the past years, several studies have identified some of these QTLs. However, because these studies only focus on a limited set of traits and often use different techniques and starting strains, a global view of industrially relevant QTLs is still missing.

RESULTS

Here, we combined the power of 1125 fully sequenced inbred segregants with high-throughput phenotyping methods to identify as many as 678 QTLs across 18 different traits relevant to industrial fermentation processes, including production of ethanol, glycerol, isobutanol, acetic acid, sulfur dioxide, flavor-active esters, as well as resistance to ethanol, acetic acid, sulfite and high osmolarity. We identified and confirmed several variants that are associated with multiple different traits, indicating that many QTLs are pleiotropic. Moreover, we show that both rare and common variants, as well as variants located in coding and non-coding regions all contribute to the phenotypic variation.

CONCLUSIONS

Our findings represent an important step in our understanding of the genetic underpinnings of industrially relevant yeast traits and open new routes to study complex genetics and genetic interactions as well as to engineer novel, superior industrial yeasts. Moreover, the major role of rare variants suggests that there is a plethora of different combinations of mutations that can be explored in genome editing.

Incorporating comparative genomics into the design-test-learn cycle of microbial strain engineering

Engineering microbes with new properties is an important goal in industrial engineering, to establish biological factories for production of biofuels, commodity chemicals and pharmaceutics. But engineering microbes to produce new compounds with high yield remains a major challenge toward economically viable production. Incorporating several modern approaches, including synthetic and systems biology, metabolic modeling and regulatory rewiring, has proven to significantly advance industrial strain engineering. This review highlights how comparative genomics can also facilitate strain engineering, by identifying novel genes and pathways, regulatory mechanisms and genetic background effects for engineering. We discuss how incorporating comparative genomics into the design-test-learn cycle of strain engineering can provide novel information that complements other engineering strategies.