Aneuploidy influences the gene expression profiles in Saccharomyces pastorianus group I and II strains during fermentation.

The lager yeasts, Saccharomyces pastorianus, are hybrids of Saccharomyces cerevisiae and Saccharomyces eubayanus and are divided into two broad groups, Group I and II. The two groups evolved from at least one common hybridisation event but have subsequently diverged with Group I strains losing many S. cerevisiae chromosomes while the Group II strains retain both sub-genomes. The complex genomes, containing orthologous alleles from the parental chromosomes, pose interesting questions regarding gene regulation and its impact on the fermentation properties of the strains. Superimposed on the presence of orthologous alleles are complexities of gene dosage due to the aneuploid nature of the genomes. We examined the contribution of the S. cerevisiae and S. eubayanus alleles to the gene expression patterns of representative Group I and II strains during fermentation. We show that the relative expression of S. cerevisiae and S. eubayanus orthologues is positively correlated with gene copy number. Despite the reduced S. cerevisiae content in the Group I strain, S. cerevisiae orthologues contribute to biochemical pathways upregulated during fermentation which may explain the retention of specific chromosomes in the strain. Conversely, S. eubayanus genes are significantly overrepresented in the upregulated gene pool in the Group II strain. Comparison of the transcription profiles of the strains during fermentation identified both common and unique gene expression patterns, with gene copy number being a dominant contributory factor. Thus, the aneuploid genomes create complex patterns of gene expression during fermentation with gene dosage playing a crucial role both within and between strains.

Functional and transcriptional profiling of non-coding RNAs in yeast reveal context-dependent phenotypes and in trans effects on the protein regulatory network.

Non-coding RNAs (ncRNAs), including the more recently identified Stable Unannotated Transcripts (SUTs) and Cryptic Unstable Transcripts (CUTs), are increasingly being shown to play pivotal roles in the transcriptional and post-transcriptional regulation of genes in eukaryotes. Here, we carried out a large-scale screening of ncRNAs in Saccharomyces cerevisiae, and provide evidence for SUT and CUT function. Phenotypic data on 372 ncRNA deletion strains in 23 different growth conditions were collected, identifying ncRNAs responsible for significant cellular fitness changes. Transcriptome profiles were assembled for 18 haploid ncRNA deletion mutants and 2 essential ncRNA heterozygous deletants. Guided by the resulting RNA-seq data we analysed the genome-wide dysregulation of protein coding genes and non-coding transcripts. Novel functional ncRNAs, SUT125, SUT126, SUT035 and SUT532 that act in trans by modulating transcription factors were identified. Furthermore, we described the impact of SUTs and CUTs in modulating coding gene expression in response to different environmental conditions, regulating important biological process such as respiration (SUT125, SUT126, SUT035, SUT432), steroid biosynthesis (CUT494, SUT053, SUT468) or rRNA processing (SUT075 and snR30). Overall, these data capture and integrate the regulatory and phenotypic network of ncRNAs and protein-coding genes, providing genome-wide evidence of the impact of ncRNAs on cellular homeostasis.

Transcriptional Profile of the Industrial Hybrid Saccharomyces pastorianus Reveals Temperature-Dependent Allele Expression Bias and Preferential Orthologous Protein Assemblies.

Saccharomyces pastorianus is a natural yeast evolved from different hybridization events between the mesophilic S. cerevisiae and the cold-tolerant S. eubayanus. This complex aneuploid hybrid carries multiple copies of the parental alleles alongside specific hybrid genes and encodes for multiple protein isoforms which impart novel phenotypes, such as the strong ability to ferment at low temperature. These characteristics lead to agonistic competition for substrates and a plethora of biochemical activities, resulting in a unique cellular metabolism. Here, we investigated the transcriptional signature of the different orthologous alleles in S. pastorianus during temperature shifts. We identified temperature-dependent media-independent genes and showed that 35% has their regulation dependent on extracellular leucine uptake, suggesting an interplay between leucine metabolism and temperature response. The analysis of the expression of ortholog parental alleles unveiled that the majority of the genes expresses preferentially one parental allele over the other and that S. eubayanus-like alleles are significantly over-represented among the genes involved in the cold acclimatization. The presence of functionally redundant parental alleles may impact on the nature of protein complexes established in the hybrid, where both parental alleles are competing. Our expression data indicate that the majority of the protein complexes investigated in the hybrid are likely to be either exclusively chimeric or unispecific and that the redundancy is discouraged, a scenario that fits well with the gene balance hypothesis. This study offers the first overview of the transcriptional pattern of S. pastorianus and provides a rationalization for its unique industrial traits at the expression level.

Development of a genome-scale metabolic model for the lager hybrid yeast S. pastorianus to understand the evolution of metabolic pathways in industrial settings.

In silico tools such as genome-scale metabolic models have shown to be powerful for metabolic engineering of microorganisms. Saccharomyces pastorianus is a complex aneuploid hybrid between the mesophilic Saccharomyces cerevisiae and the cold-tolerant Saccharomyces eubayanus. This species is of biotechnological importance because it is the primary yeast used in lager beer fermentation and is also a key model for studying the evolution of hybrid genomes, including expression pattern of ortholog genes, composition of protein complexes, and phenotypic plasticity. Here, we created the iSP_1513 GSMM for S. pastorianus CBS1513 to allow top-down computational approaches to predict the evolution of metabolic pathways and to aid strain optimization in production processes. The iSP_1513 comprises 4,062 reactions, 1,808 alleles, and 2,747 metabolites, and takes into account the functional redundancy in the gene-protein-reaction rule caused by the presence of orthologous genes. Moreover, a universal algorithm to constrain GSMM reactions using transcriptome data was developed as a python library and enabled the integration of temperature as parameter. Essentiality data sets, growth data on various carbohydrates and volatile metabolites secretion were used to validate the model and showed the potential of media engineering to improve specific flavor compounds. The iSP_1513 also highlighted the different contributions of the parental sub-genomes to the oxidative and non-oxidative parts of the pentose phosphate pathway. Overall, the iSP_1513 GSMM represent an important step toward understanding the metabolic capabilities, evolutionary trajectories, and adaptation potential of S. pastorianus in different industrial settings. IMPORTANCE: Genome-scale metabolic models (GSMM) have been successfully applied to predict cellular behavior and design cell factories in several model organisms, but no models to date are currently available for hybrid species due to their more complex genetics and general lack of molecular data. In this study, we generated a bespoke GSMM, iSP_1513, for this industrial aneuploid hybrid Saccharomyces pastorianus, which takes into account the aneuploidy and functional redundancy from orthologous parental alleles. This model will (i) help understand the metabolic capabilities and adaptive potential of S. pastorianus (domestication processes), (ii) aid top-down predictions for strain development (industrial biotechnology), and (iii) allow predictions of evolutionary trajectories of metabolic pathways in aneuploid hybrids (evolutionary genetics).

High quality de novo genome assembly of the non-conventional yeast Kazachstania bulderi describes a potential low pH production host for biorefineries.

Kazachstania bulderi is a non-conventional yeast species able to grow efficiently on glucose and δ-gluconolactone at low pH. These unique traits make K. bulderi an ideal candidate for use in sustainable biotechnology processes including low pH fermentations and the production of green chemicals including organic acids. To accelerate strain development with this species, detailed information of its genetics is needed. Here, by employing long read sequencing we report a high-quality phased genome assembly for three strains of K. bulderi species, including the type strain. The sequences were assembled into 12 chromosomes with a total length of 14 Mb, and the genome was fully annotated at structural and functional levels, including allelic and structural variants, ribosomal array and mating type locus. This high-quality reference genome provides a resource to advance our fundamental knowledge of biotechnologically relevant non-conventional yeasts and to support the development of genetic tools for manipulating such strains towards their use as production hosts in biotechnological processes.

HybridMine: A Pipeline for Allele Inheritance and Gene Copy Number Prediction in Hybrid Genomes and Its Application to Industrial Yeasts.

Genome-scale computational approaches are opening opportunities to model and predict favorable combination of traits for strain development. However, mining the genome of complex hybrids is not currently an easy task, due to the high level of redundancy and presence of homologous. For example, Saccharomyces pastorianus is an allopolyploid sterile yeast hybrid used in brewing to produce lager-style beers. The development of new yeast strains with valuable industrial traits such as improved maltose utilization or balanced flavor profiles are now a major ambition and challenge in craft brewing and distilling industries. Moreover, no genome annotation for most of these industrial strains have been published. Here, we developed HybridMine, a new user-friendly, open-source tool for functional annotation of hybrid aneuploid genomes of any species by predicting parental alleles including paralogs. Our benchmark studies showed that HybridMine produced biologically accurate results for hybrid genomes compared to other well-established software. As proof of principle, we carried out a comprehensive structural and functional annotation of complex yeast hybrids to enable system biology prediction studies. HybridMine is developed in Python, Perl, and Bash programming languages and is available in GitHub.