Interpreting protein abundance in Saccharomyces cerevisiae through relational learning.

MOTIVATION: Proteomic profiles reflect the functional readout of the physiological state of an organism. An increased understanding of what controls and defines protein abundances is of high scientific interest. Saccharomyces cerevisiae is a well-studied model organism, and there is a large amount of structured knowledge on yeast systems biology in databases such as the Saccharomyces Genome Database, and highly curated genome-scale metabolic models like Yeast8. These datasets, the result of decades of experiments, are abundant in information, and adhere to semantically meaningful ontologies. RESULTS: By representing this knowledge in an expressive Datalog database we generated data descriptors using relational learning that, when combined with supervised machine learning, enables us to predict protein abundances in an explainable manner. We learnt predictive relationships between protein abundances, function and phenotype; such as α-amino acid accumulations and deviations in chronological lifespan. We further demonstrate the power of this methodology on the proteins His4 and Ilv2, connecting qualitative biological concepts to quantified abundances. AVAILABILITY AND IMPLEMENTATION: All data and processing scripts are available at the following Github repository: https://github.com/DanielBrunnsaker/ProtPredict.

Genome-scale model of Rhodotorula toruloides metabolism.

The basidiomycete red yeast Rhodotorula toruloides is a promising platform organism for production of biooils. We present rhto-GEM, the first genome-scale model (GEM) of R. toruloides metabolism, that was largely reconstructed using RAVEN toolbox. The model includes 852 genes, 2,731 reactions, and 2,277 metabolites, while lipid metabolism is described using the SLIMEr formalism allowing direct integration of lipid class and acyl chain experimental distribution data. The simulation results confirmed that the R. toruloides model provides valid growth predictions on glucose, xylose, and glycerol, while prediction of genetic engineering targets to increase production of linolenic acid, triacylglycerols, and carotenoids identified genes-some of which have previously been engineered to successfully increase production. This renders rtho-GEM valuable for future studies to improve the production of other oleochemicals of industrial relevance including value-added fatty acids and carotenoids, in addition to facilitate system-wide omics-data analysis in R. toruloides. Expanding the portfolio of GEMs for lipid-accumulating fungi contributes to both understanding of metabolic mechanisms of the oleaginous phenotype but also uncover particularities of the lipid production machinery in R. toruloides.

Adaptation of Dekkera bruxellensis to lignocellulose-based substrate.

Adaptation of Dekkera bruxellensis to lignocellulose hydrolysate was investigated. Cells of D. bruxellensis were grown for 72 and 192 H in batch and continuous culture, respectively (adapted cells). Cultivations in semisynthetic medium were run as controls (nonadapted cells). To test the adaptation, cells from these cultures were reinoculated in the lignocellulose medium, and growth and ethanol production characteristics were monitored. Cells adapted to lignocellulose hydrolysate had a shorter lag phase, grew faster, and produced a higher ethanol concentration as compared with nonadapted cells. A stability test showed that after cultivation in rich medium, cells partially lost the adapted phenotype but still showed faster growth and higher ethanol production as compared with nonadapted cells. Because alcohol dehydrogenase genes have been described to be involved in the adaptation to furfural in Saccharomyces cerevisiae, an analogous mechanism of adaptation to lignocelluloses hydrolysate of D. bruxellensis was hypothesized. However, gene expression analysis showed that genes homologous to S. cerevisiae ADH1 were not involved in the adaptation to lignocelluloses hydrolysate in D. bruxellensis.

High-throughput metabolomics for the design and validation of a diauxic shift model.

Saccharomyces cerevisiae is a very well studied organism, yet ∼20% of its proteins remain poorly characterized. Moreover, recent studies seem to indicate that the pace of functional discovery is slow. Previous work has implied that the most probable path forward is via not only automation but fully autonomous systems in which active learning is applied to guide high-throughput experimentation. Development of tools and methods for these types of systems is of paramount importance. In this study we use constrained dynamical flux balance analysis (dFBA) to select ten regulatory deletant strains that are likely to have previously unexplored connections to the diauxic shift. We then analyzed these deletant strains using untargeted metabolomics, generating profiles which were then subsequently investigated to better understand the consequences of the gene deletions in the metabolic reconfiguration of the diauxic shift. We show that metabolic profiles can be utilised to not only gaining insight into cellular transformations such as the diauxic shift, but also on regulatory roles and biological consequences of regulatory gene deletion. We also conclude that untargeted metabolomics is a useful tool for guidance in high-throughput model improvement, and is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of genes. Moreover, it is well-suited for automated approaches due to relative simplicity of processing and the potential to make massively high-throughput.

Proteome analysis of xylose metabolism in Rhodotorula toruloides during lipid production.

BACKGROUND: Rhodotorula toruloides is a promising platform organism for production of lipids from lignocellulosic substrates. Little is known about the metabolic aspects of lipid production from the lignocellolosic sugar xylose by oleaginous yeasts in general and R. toruloides in particular. This study presents the first proteome analysis of the metabolism of R. toruloides during conversion of xylose to lipids. RESULTS: Rhodotorula toruloides cultivated on either glucose or xylose was subjected to comparative analysis of its growth dynamics, lipid composition, fatty acid profiles and proteome. The maximum growth and sugar uptake rate of glucose-grown R. toruloides cells were almost twice that of xylose-grown cells. Cultivation on xylose medium resulted in a lower final biomass yield although final cellular lipid content was similar between glucose- and xylose-grown cells. Analysis of lipid classes revealed the presence of monoacylglycerol in the early exponential growth phase as well as a high proportion of free fatty acids. Carbon source-specific changes in lipid profiles were only observed at early exponential growth phase, where C18 fatty acids were more saturated in xylose-grown cells. Proteins involved in sugar transport, initial steps of xylose assimilation and NADPH regeneration were among the proteins whose levels increased the most in xylose-grown cells across all time points. The levels of enzymes involved in the mevalonate pathway, phospholipid biosynthesis and amino acids biosynthesis differed in response to carbon source. In addition, xylose-grown cells contained higher levels of enzymes involved in peroxisomal beta-oxidation and oxidative stress response compared to cells cultivated on glucose. CONCLUSIONS: The results obtained in the present study suggest that sugar import is the limiting step during xylose conversion by R. toruloides into lipids. NADPH appeared to be regenerated primarily through pentose phosphate pathway although it may also involve malic enzyme as well as alcohol and aldehyde dehydrogenases. Increases in enzyme levels of both fatty acid biosynthesis and beta-oxidation in xylose-grown cells was predicted to result in a futile cycle. The results presented here are valuable for the development of lipid production processes employing R. toruloides on xylose-containing substrates.

Chromosomal genome assembly of the ethanol production strain CBS 11270 indicates a highly dynamic genome structure in the yeast species Brettanomyces bruxellensis.

Here, we present the genome of the industrial ethanol production strain Brettanomyces bruxellensis CBS 11270. The nuclear genome was found to be diploid, containing four chromosomes with sizes of ranging from 2.2 to 4.0 Mbp. A 75 Kbp mitochondrial genome was also identified. Comparing the homologous chromosomes, we detected that 0.32% of nucleotides were polymorphic, i.e. formed single nucleotide polymorphisms (SNPs), 40.6% of them were found in coding regions (i.e. 0.13% of all nucleotides formed SNPs and were in coding regions). In addition, 8,538 indels were found. The total number of protein coding genes was 4897, of them, 4,284 were annotated on chromosomes; and the mitochondrial genome contained 18 protein coding genes. Additionally, 595 genes, which were annotated, were on contigs not associated with chromosomes. A number of genes was duplicated, most of them as tandem repeats, including a six-gene cluster located on chromosome 3. There were also examples of interchromosomal gene duplications, including a duplication of a six-gene cluster, which was found on both chromosomes 1 and 4. Gene copy number analysis suggested loss of heterozygosity for 372 genes. This may reflect adaptation to relatively harsh but constant conditions of continuous fermentation. Analysis of gene topology showed that most of these losses occurred in clusters of more than one gene, the largest cluster comprising 33 genes. Comparative analysis against the wine isolate CBS 2499 revealed 88,534 SNPs and 8,133 indels. Moreover, when the scaffolds of the CBS 2499 genome assembly were aligned against the chromosomes of CBS 11270, many of them aligned completely, some have chunks aligned to different chromosomes, and some were in fact rearranged. Our findings indicate a highly dynamic genome within the species B. bruxellensis and a tendency towards reduction of gene number in long-term continuous cultivation.

Identification and characterisation of two high-affinity glucose transporters from the spoilage yeast Brettanomyces bruxellensis.

The yeast Brettanomyces bruxellensis (syn. Dekkera bruxellensis) is an emerging and undesirable contaminant in industrial low-sugar ethanol fermentations that employ the yeast Saccharomyces cerevisiae. High-affinity glucose import in B. bruxellensis has been proposed to be the mechanism by which this yeast can outcompete S. cerevisiae. The present study describes the characterization of two B. bruxellensis genes (BHT1 and BHT3) believed to encode putative high-affinity glucose transporters. In vitro-generated transcripts of both genes as well as the S. cerevisiae HXT7 high-affinity glucose transporter were injected into Xenopus laevis oocytes and subsequent glucose uptake rates were assayed using 14C-labelled glucose. At 0.1 mM glucose, Bht1p was shown to transport glucose five times faster than Hxt7p. pH affected the rate of glucose transport by Bht1p and Bht3p, indicating an active glucose transport mechanism that involves proton symport. These results suggest a possible role for BHT1 and BHT3 in the competitive ability of B. bruxellensis.

Assembly and Analysis of the Genome Sequence of the Yeast Brettanomyces naardenensis CBS 7540.

Brettanomyces naardenensis is a spoilage yeast with potential for biotechnological applications for production of innovative beverages with low alcohol content and high attenuation degree. Here, we present the first annotated genome of B. naardenensis CBS 7540. The genome of B. naardenensis CBS 7540 was assembled into 76 contigs, totaling 11,283,072 nucleotides. In total, 5168 protein-coding sequences were annotated. The study provides functional genome annotation, phylogenetic analysis, and discusses genetic determinants behind notable stress tolerance and biotechnological potential of B. naardenensis.

Transcriptome of the alternative ethanol production strain Dekkera bruxellensis CBS 11270 in sugar limited, low oxygen cultivation.

Dekkera bruxellensis can outcompete Saccharomyces cerevisiae in environments with low sugar concentrations. It is usually regarded as a spoilage yeast but has lately been identified as an alternative ethanol production organism. In this study, global gene expression in the industrial isolate D. bruxellensis CBS 11270 under oxygen and glucose limitation was investigated by whole transcriptome sequencing using the AB SOLiD technology. Among other observations, we noted expression of respiratory complex I NADH-ubiquinone reductase although D. bruxellensis is a Crabtree positive yeast. The observed higher expression of NADH-generating enzymes compared to NAD(+)-generating enzymes might be the reason for the previously observed NADH imbalance and resulting Custer effect in D. bruxellensis. Low expression of genes involved in glycerol production is probably the molecular basis for high efficiency of D. bruxellensis metabolism under nutrient limitation. No D. bruxellensis homologs to the genes involved in the final reactions of glycerol biosynthesis were detected. A high number of expressed sugar transporter genes is consistent with the hypothesis that the competitiveness of D. bruxellensis is due to a higher affinity for the limiting substrate.