The basidiomycete yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides) accumulates high concentrations of lipids and carotenoids from diverse carbon sources. It has great potential as a model for the cellular biology of lipid droplets and for sustainable chemical production. We developed a method for high-throughput genetics (RB-TDNAseq), using sequence-barcoded Agrobacterium tumefaciens T-DNA insertions. We identified 1,337 putative essential genes with low T-DNA insertion rates. We functionally profiled genes required for fatty acid catabolism and lipid accumulation, validating results with 35 targeted deletion strains. We identified a high-confidence set of 150 genes affecting lipid accumulation, including genes with predicted function in signaling cascades, gene expression, protein modification and vesicular trafficking, autophagy, amino acid synthesis and tRNA modification, and genes of unknown function. These results greatly advance our understanding of lipid metabolism in this oleaginous species and demonstrate a general approach for barcoded mutagenesis that should enable functional genomics in diverse fungi.

Spent sulfite liquor (SSL) is a waste effluent from sulfite pulping that contains monomeric sugars which can be fermented to ethanol. However, fermentative yeasts used for the fermentation of the sugars in SSL are adversely affected by the inhibitory substances in this complex feedstock. To overcome this limitation, evolutionary engineering of Saccharomyces cerevisiae was carried out using genome-shuffling technology based on large-scale population cross mating. Populations of UV-light-induced yeast mutants more tolerant than the wild type to hardwood spent sulfite liquor (HWSSL) were first isolated and then recursively mated and enriched for more-tolerant populations. After five rounds of genome shuffling, three strains were isolated that were able to grow on undiluted HWSSL and to support efficient ethanol production from the sugars therein for prolonged fermentation of HWSSL. Analyses showed that greater HWSSL tolerance is associated with improved viability in the presence of salt, sorbitol, peroxide, and acetic acid. Our results showed that evolutionary engineering through genome shuffling will yield robust yeasts capable of fermenting the sugars present in HWSSL, which is a complex substrate containing multiple sources of inhibitors. These strains may not be obtainable through classical evolutionary engineering and can serve as a model for further understanding of the mechanism behind simultaneous tolerance to multiple inhibitors.

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Mutants of Pichia stipitis NRRL Y-7124 able to tolerate and produce ethanol from hardwood spent sulfite liquor (HW SSL) were obtained by UV mutagenesis. P. stipitis cells were subjected to three successive rounds of UV mutagenesis, each followed by screening first on HW SSL gradient plates and then in diluted liquid HW SSL. Six third generation mutants with greater tolerance to HW SSL as compared to the wild type (WT) were isolated. The WT strain could not grow in HW SSL unless it was diluted to 65% (v/v). In contrast, the third generation mutants were able to grow in HW SSL diluted to 75% (v/v). Mutants PS301 and PS302 survived even in 80% (v/v) HW SSL, although there was no increase in cell number. All the third generation mutants exhibited higher growth rates but significantly lower growth yields on xylose or glucose compared to the WT. The mutants fermented 4% (w/v) glucose as efficiently as the WT and fermented 4% (w/v) xylose more efficiently with a higher ethanol yield than the WT. In a medium containing 4% (w/v) each of xylose and glucose, all the third generation mutants utilized glucose as efficiently and xylose more efficiently than the WT. This resulted in higher ethanol yield by the mutants. The mutants retained the ability to utilize galactose and mannose and ferment them to ethanol. Arabinose was consumed slowly by both the mutants and WT with no ethanol production. In 60% (v/v) HW SSL, the mutants utilized and fermented glucose, mannose, galactose and xylose while the WT could not ferment any of these sugars.

Coenzyme Q10 has emerged as a valuable molecule for pharmaceutical and cosmetic applications. Therefore, research into producing and optimizing coenzyme Q10 via microbial fermentation is ongoing. There are two major paths being explored for maximizing production of this molecule to commercially advantageous levels. The first entails using microbes that naturally produce coenzyme Q10 as fermentation biocatalysts and optimizing the fermentation parameters in order to reach industrial levels of production. However, the natural coenzyme Q10-producing microbes tend to be intractable for industrial fermentation settings. The second path to coenzyme Q10 production being explored is to engineer Escherichia coli with the ability to biosynthesize this molecule in order to take advantage of its more favourable fermentation characteristics and the well-understood array of genetic tools available for this bacteria. Although many studies have attempted to over-produce coenzyme Q10 in E. coli through genetic engineering, production titres still remain below those of the natural coenzyme Q10-producing microorganisms. Current research is providing the knowledge needed to alleviate the bottlenecks involved in producing coenzyme Q10 from an E. coli strain platform and the fermentation parameters that could dramatically increase production titres from natural microbial producers. Synthesizing the lessons learned from both approaches may be the key towards a more cost-effective coenzyme Q10 industry.

BackgroundIdentifying the genetic basis of complex microbial phenotypes is currently a major barrier to our understanding of multigenic traits and our ability to rationally design biocatalysts with highly specific attributes for the biotechnology industry. Here, we demonstrate that strain evolution by meiotic recombination-based genome shuffling coupled with deep sequencing can be used to deconstruct complex phenotypes and explore the nature of multigenic traits, while providing concrete targets for strain development.ResultsWe determined genomic variations found within Saccharomyces cerevisiae previously evolved in our laboratory by genome shuffling for tolerance to spent sulphite liquor. The representation of these variations was backtracked through parental mutant pools and cross-referenced with RNA-seq gene expression analysis to elucidate the importance of single mutations and key biological processes that play a role in our trait of interest. Our findings pinpoint novel genes and biological determinants of lignocellulosic hydrolysate inhibitor tolerance in yeast. These include the following: protein homeostasis constituents, including Ubp7p and Art5p, related to ubiquitin-mediated proteolysis; stress response transcriptional repressor, Nrg1p; and NADPH-dependent glutamate dehydrogenase, Gdh1p. Reverse engineering a prominent mutation in ubiquitin-specific protease gene UBP7 in a laboratory S. cerevisiae strain effectively increased spent sulphite liquor tolerance.ConclusionsThis study advances understanding of yeast tolerance mechanisms to inhibitory substrates and biocatalyst design for a biomass-to-biofuel/biochemical industry, while providing insights into the process of mutation accumulation that occurs during genome shuffling.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-015-0241-z) contains supplementary material, which is available to authorized users.

Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.

BackgroundGenome shuffling (GS) is a widely adopted methodology for the evolutionary engineering of desirable traits in industrially relevant microorganisms. We have previously used genome shuffling to generate a strain of Saccharomyces cerevisiae that is tolerant to the growth inhibitors found in a lignocellulosic hydrolysate. In this study, we expand on previous work by performing a population-wide genomic survey of our genome shuffling experiment and dissecting the molecular determinants of the evolved phenotype.ResultsWhole population whole-genome sequencing was used to survey mutations selected during the experiment and extract allele frequency time series. Using growth curve assays on single point mutants and backcrossed derivatives, we explored the genetic architecture of the selected phenotype and detected examples of epistasis. Our results reveal cohorts of strongly correlated mutations, suggesting prevalent genetic hitchhiking and the presence of pre-existing founder mutations. From the patterns of apparent selection and the results of direct phenotypic assays, our results identify key driver mutations and deleterious hitchhikers.ConclusionsWe use these data to propose a model of inhibitor tolerance in our GS mutants. Our results also suggest a role for compensatory evolution and epistasis in our genome shuffling experiment and illustrate the impact of historical contingency on the outcomes of evolutionary engineering.Electronic supplementary materialThe online version of this article (10.1186/s13068-018-1283-9) contains supplementary material, which is available to authorized users.