| 1. |
- Madsen, Karina M., et al.
(författare)
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Linking Genotype and Phenotype of Saccharomyces cerevisiae Strains Reveals Metabolic Engineering Targets and Leads to Triterpene Hyper-Producers
- 2011
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 6:3, s. e14763-
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundMetabolic engineering is an attractive approach in order to improve the microbial production of drugs. Triterpenes is a chemically diverse class of compounds and many among them are of interest from a human health perspective. A systematic experimental or computational survey of all feasible gene modifications to determine the genotype yielding the optimal triterpene production phenotype is a laborious and time-consuming process.Methodology/Principal FindingsBased on the recent genome-wide sequencing of Saccharomyces cerevisiae CEN.PK 113-7D and its phenotypic differences with the S288C strain, we implemented a strategy for the construction of a β-amyrin production platform. The genes Erg8, Erg9 and HFA1 contained non-silent SNPs that were computationally analyzed to evaluate the changes that cause in the respective protein structures. Subsequently, Erg8, Erg9 and HFA1 were correlated with the increased levels of ergosterol and fatty acids in CEN.PK 113-7D and single, double, and triple gene over-expression strains were constructed.ConclusionsThe six out of seven gene over-expression constructs had a considerable impact on both ergosterol and β-amyrin production. In the case of β-amyrin formation the triple over-expression construct exhibited a nearly 500% increase over the control strain making our metabolic engineering strategy the most successful design of triterpene microbial producers.
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| 2. |
- Otero, José Manuel, 1979, et al.
(författare)
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Industrial Systems Biology
- 2010
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Ingår i: Biotechnology and Bioengineering. - : Wiley. - 0006-3592 .- 1097-0290. ; 105:3, s. 439-460
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Tidskriftsartikel (refereegranskat)abstract
- The chemical industry is currently undergoing a dramatic change driven by demand for developing more sustainable processes for the production of fuels, chemicals, and materials. In biotechnological processes different microorganisms can be exploited, and the large diversity of metabolic reactions represents a rich repository for the design of chemical conversion processes that lead to efficient production of desirable products. However, often microorganisms that produce a desirable product, either naturally or because they have been engineered through insertion of heterologous Pathways, have low yields and productivities, and in order to establish an economically viable process it is necessary to improve the performance of the microorganism. Here metabolic engineering is the enabling technology. Through metabolic engineering the metabolic landscape of the microorganism is engineered such that there is an efficient conversion of the raw material, typically glucose, to the product of interest. This process may involve both insertion of new enzymes activities, deletion of existing enzyme activities, but often also deregulation of existing regulatory structures operating in the cell. In order to rapidly identify the optimal metabolic engineering strategy the industry is to an increasing extent looking into the use of tools from systems biology. This involves both x-ome technologies such as transcriptome, proteome, metabolome, and fluxome analysis, and advanced mathematical modeling tools Such is genome-scale metabolic modeling. Here we look into the history of these different techniques and review how they find application in industrial biotechnology, which will lead to what we here define as industrial systems biology.
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| 3. |
- Otero, José Manuel, 1979, et al.
(författare)
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Industrial Systems Biology
- 2010
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Ingår i: Industrial Biotechnology: Sustainable Growth and Economic Success. - Weinheim, Germany : Wiley-VCH Verlag GmbH & Co. KGaA. - 9783527314423 ; , s. 79-147
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 4. |
- Otero, José Manuel, 1979
(författare)
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Industrial Systems Biology and Metabolic Engineering of Saccharomyces cerevisiae
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factoryfor the largest industrial biotechnology product (bioethanol), and a robust commercially compatible scaffold to be exploited for diverse chemical production. Succinic acid is a highly sought after added-value chemical whichis not overproduced in native S. cerevisiae strains. The genome-scale metabolic network reconstruction of S.cerevisiae enabled in silico gene deletion predictions. First, a multi-gene, non-intuitive, genetic engineeringstrategy guided by an evolutionary programming method to couple biomass formation through glycine/serineamino acid requirements to succinate production was proposed. Pursuing these targets, a multi-gene deletionstrain was constructed, and directed evolution with selection was used to identify a succinate producing mutant.Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolicallyengineered strain were used to identify 2nd-round metabolic engineering targets – overexpression of ICL1. Theresulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Further genome-scale metabolic modeling supplemented with pathway visualization, flux balance analysis, and modelmodifications to better simulate batch glucose conditions was performed. Identification of the top single anddouble gene deletion strategies, under aerobic and anaerobic conditions, resulted in three predictions with a 10-fold improvement in succinate yield on glucose compared to the reference: MDH1, OAC1, and DIC1. While⊿mdh1 and ⊿oac1 strains failed to produce more succinate relative to the reference, ⊿dic1 produced 0.02 C-mol C-mol-glucose-1, in close agreement with model predictions (0.03 C-mol C-mol-glucose-1). Pathwayvisualization, coupled with transcriptional profiling, suggested that succinate formation was coupled tomitochondrial redox balancing, and more specifically, reductive TCA cycle activity. The aforementionedmetabolic engineering strategies were designed based on glucose supplementation and metabolism. Future S.cerevisiae microbial cell factories capable of fast and efficient xylose consumption for biorefinery compatibility,and succinic acid overproduction would be highly desirable. Metabolic engineering of S. cerevisiae forconsumption of xylose aerobically without redirection of some carbon flux to overflow metabolites (ethanol,glycerol, acetate, xylitol) was accomplished by expression of PsXYL1, PsXYL2, and PsXYL3 from the nativexylose-metabolizing Pichia stipitis, and subsequent, directed evolution. The resulting S. cerevisiae strain showed xylose consumption at a specific rate of 0.31 g g-cell-1 h-1, a specific growth rate of 0.18 h-1, and a biomass yieldof 0.62 C-mol C-mol-xylose-1. Plasmid isolation and re-transformation confirmed the conferred phenotyperesulted from a chromosomal modification. Transcriptional profiling confirmed a strongly up-regulatedglyoxylate pathway enabling sustained respiratory metabolism. A proof-of-concept study was performed todetermine if whole high-throughput genome sequencing could be used as a tool in metabolic engineering fordirect identification of genotype to phenotype correlations. Therefore, whole genome sequencing of S.cerevisiae S288C and CEN.PK113-7D resulted in identification of 13,787 filtered SNPs in CEN.PK113-7D,with a total of 939 SNPs detected across 158 unique metabolic genes, 85 of which contained a total of 219 nonsilentSNPs. S. cerevisiae CEN.PK113-7D exhibited significantly higher ergosterol content correlating withnon-silent SNPs identified in ERG8 and ERG9. The flux through the galactose uptake pathway was much lowerin S288C compared with CEN.PK113-7D, correlating with the non-silent SNP enrichment in GAL1 and GAL10.Inspection of the significantly differentially expressed genes between strains did not reveal an obvious genecluster that would explain the significant physiological differences, strongly suggesting that genotype tophenotype correlation is manifested post-transcriptionally or post-translationally.
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| 5. |
- Otero, José Manuel, 1979, et al.
(författare)
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Industrial Systems Biology of Saccharomyces cerevisiae Enables Novel Succinic Acid Cell Factory
- 2013
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the alpha-keto-glutarate dehydrogenase catalyzed conversion of alpha-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals.
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| 6. |
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| 7. |
- Otero, José Manuel, 1979, et al.
(författare)
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Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications
- 2010
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 11:1, s. 723-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The need for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering.Results: In this work we performed whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between Saccharomyces cerevisiae strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the Saccharomyces Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,596 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being nonsynonymous (e. g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (GAL1, GAL10) and ergosterol biosynthetic pathway (ERG8, ERG9). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function.Conclusions: With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at http://www.sysbio.se/cenpk.
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| 8. |
- Otero, José Manuel, 1979, et al.
(författare)
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Yeast Biological Networks Unfold the Interplay of Antioxidants, Genome and Phenotype, and Reveal a Novel Regulator of the Oxidative Stress Response
- 2010
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 5:10, s. e13606-
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundIdentifying causative biological networks associated with relevant phenotypes is essential in the field of systems biology. We used ferulic acid (FA) as a model antioxidant to characterize the global expression programs triggered by this small molecule and decipher the transcriptional network controlling the phenotypic adaptation of the yeast Saccharomyces cerevisiae.Methodology/Principal FindingsBy employing a strict cut off value during gene expression data analysis, 106 genes were found to be involved in the cell response to FA, independent of aerobic or anaerobic conditions. Network analysis of the system guided us to a key target node, the FMP43 protein, that when deleted resulted in marked acceleration of cellular growth (~15% in both minimal and rich media). To extend our findings to human cells and identify proteins that could serve as drug targets, we replaced the yeast FMP43 protein with its human ortholog BRP44 in the genetic background of the yeast strain Δfmp43. The conservation of the two proteins was phenotypically evident, with BRP44 restoring the normal specific growth rate of the wild type. We also applied homology modeling to predict the 3D structure of the FMP43 and BRP44 proteins. The binding sites in the homology models of FMP43 and BRP44 were computationally predicted, and further docking studies were performed using FA as the ligand. The docking studies demonstrated the affinity of FA towards both FMP43 and BRP44.ConclusionsThis study proposes a hypothesis on the mechanisms yeast employs to respond to antioxidant molecules, while demonstrating how phenome and metabolome yeast data can serve as biomarkers for nutraceutical discovery and development. Additionally, we provide evidence for a putative therapeutic target, revealed by replacing the FMP43 protein with its human ortholog BRP44, a brain protein, and functionally characterizing the relevant mutant strain.
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| 9. |
- Scalcinati, Gionata, 1981, et al.
(författare)
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Evolutionary engineering of Saccharomyces cerevisiae for efficient aerobic xylose consumption
- 2012
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Ingår i: FEMS Yeast Research. - : Oxford University Press (OUP). - 1567-1356 .- 1567-1364. ; 12:5, s. 582-597
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Tidskriftsartikel (refereegranskat)abstract
- Industrial biotechnology aims to develop robust microbial cell factories, such as Saccharomyces cerevisiae, to produce an array of added value chemicals presently dominated by petrochemical processes. Xylose is the second most abundant monosaccharide after glucose and the most prevalent pentose sugar found in lignocelluloses. Significant research efforts have focused on the metabolic engineering of S similar to cerevisiae for fast and efficient xylose utilization. This study aims to metabolically engineer S similar to cerevisiae, such that it can consume xylose as the exclusive substrate while maximizing carbon flux to biomass production. Such a platform may then be enhanced with complementary metabolic engineering strategies that couple biomass production with high value-added chemical. Saccharomyces cerevisiae, expressing xylose reductase, xylitol dehydrogenase and xylulose kinase, from the native xylose-metabolizing yeast Pichia stipitis, was constructed, followed by a directed evolution strategy to improve xylose utilization rates. The resulting S similar to cerevisiae strain was capable of rapid growth and fast xylose consumption producing only biomass and negligible amount of byproducts. Transcriptional profiling of this strain was employed to further elucidate the observed physiology confirms a strongly up-regulated glyoxylate pathway enabling respiratory metabolism. The resulting strain is a desirable platform for the industrial production of biomass-related products using xylose as a sole carbon source.
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| 10. |
- Ågren, Rasmus, 1982, et al.
(författare)
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Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production
- 2013
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Ingår i: Journal of Industrial Microbiology and Biotechnology. - : Oxford University Press (OUP). - 1367-5435 .- 1476-5535. ; 40:7, s. 735-747
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Tidskriftsartikel (refereegranskat)abstract
- In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Delta mdh1, Delta oac1, and Delta dic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Delta mdh1 and Delta oac1 strains failed to produce succinate, Delta dic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.
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