| 1. |
|
|
| 2. |
- Kildegaard, K. R., et al.
(author)
-
Engineering and systems-level analysis of Saccharomyces cerevisiae for production of 3-hydroxypropionic acid via malonyl-CoA reductase-dependent pathway
- 2016
-
In: Microbial Cell Factories. - : Springer Science and Business Media LLC. - 1475-2859. ; 15:1
-
Journal article (peer-reviewed)abstract
- Background: In the future, oil-and gas-derived polymers may be replaced with bio-based polymers, produced from renewable feedstocks using engineered cell factories. Acrylic acid and acrylic esters with an estimated world annual production of approximately 6 million tons by 2017 can be derived from 3-hydroxypropionic acid (3HP), which can be produced by microbial fermentation. For an economically viable process 3HP must be produced at high titer, rate and yield and preferably at low pH to minimize downstream processing costs. Results: Here we describe the metabolic engineering of baker's yeast Saccharomyces cerevisiae for biosynthesis of 3HP via a malonyl-CoA reductase (MCR)-dependent pathway. Integration of multiple copies of MCR from Chloroflexus aurantiacus and of phosphorylation-deficient acetyl-CoA carboxylase ACC1 genes into the genome of yeast increased 3HP titer fivefold in comparison with single integration. Furthermore we optimized the supply of acetyl-CoA by overexpressing native pyruvate decarboxylase PDC1, aldehyde dehydrogenase ALD6, and acetyl-CoA synthase from Salmonella enterica SEacsL641P. Finally we engineered the cofactor specificity of the glyceraldehyde-3-phosphate dehydrogenase to increase the intracellular production of NADPH at the expense of NADH and thus improve 3HP production and reduce formation of glycerol as by-product. The final strain produced 9.8 +/- 0.4 g L-1 3HP with a yield of 13 % C-mol C-mol(-1) glucose after 100 h in carbon-limited fed-batch cultivation at pH 5. The 3HP-producing strain was characterized by C-13 metabolic flux analysis and by transcriptome analysis, which revealed some unexpected consequences of the undertaken metabolic engineering strategy, and based on this data, future metabolic engineering directions are proposed. Conclusions: In this study, S. cerevisiae was engineered for high-level production of 3HP by increasing the copy numbers of biosynthetic genes and improving flux towards precursors and redox cofactors. This strain represents a good platform for further optimization of 3HP production and hence an important step towards potential commercial bio-based production of 3HP.
|
|
| 3. |
- Maury, J., et al.
(author)
-
EasyCloneMulti: A Set of Vectors for Simultaneous and Multiple Genomic Integrations in Saccharomyces cerevisiae
- 2016
-
In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 11:3
-
Journal article (peer-reviewed)abstract
- Saccharomyces cerevisiae is widely used in the biotechnology industry for production of ethanol, recombinant proteins, food ingredients and other chemicals. In order to generate highly producing and stable strains, genome integration of genes encoding metabolic pathway enzymes is the preferred option. However, integration of pathway genes in single or few copies, especially those encoding rate-controlling steps, is often not sufficient to sustain high metabolic fluxes. By exploiting the sequence diversity in the long terminal repeats (LTR) of Ty retrotransposons, we developed a new set of integrative vectors, EasyCloneMulti, that enables multiple and simultaneous integration of genes in S. cerevisiae. By creating vector backbones that combine consensus sequences that aim at targeting subsets of Ty sequences and a quickly degrading selective marker, integrations at multiple genomic loci and a range of expression levels were obtained, as assessed with the green fluorescent protein (GFP) reporter system. The EasyCloneMulti vector set was applied to balance the expression of the rate-controlling step in the beta-alanine pathway for biosynthesis of 3-hydroxypropionic acid (3HP). The best 3HP producing clone, with 5.45 g.L-1 of 3HP, produced 11 times more 3HP than the lowest producing clone, which demonstrates the capability of EasyCloneMulti vectors to impact metabolic pathway enzyme activity.
|
|
| 4. |
- Borodina, I., et al.
(author)
-
Establishing a synthetic pathway for high-level production of 3-hydroxypropionic acid in Saccharomyces cerevisiae via beta-alanine
- 2015
-
In: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 27, s. 57-64
-
Journal article (peer-reviewed)abstract
- Microbial fermentation of renewable feedstocks into plastic monomers can decrease our fossil dependence and reduce global CO2 emissions. 3-Hydroxypropionic acid (3HP) is a potential chemical building block for sustainable production of superabsorbent polymers and acrylic plastics. With the objective of developing Saccharolnyces cerevisiae as an efficient cell factory for high-level production of 3HP, we identified the beta-alanine biosynthetic route as the most economically attractive according to the metabolic modeling. We engineered and optimized a synthetic pathway for de novo biosynthesis of beta-alanine and its subsequent conversion into 3HP using a novel beta-alanine-pyruvate aminotransferase discovered in Bacillus cereus. The final strain produced 3HP at a titer of 13.7 +/- 0.3 g L-1 with a 0.14 +/- 0.0 C-mol C-mol(-1) yield on glucose in 80 h in controlled fed-batch fermentation in mineral medium at pH 5, and this work therefore lays the basis for developing a process for biological 3HP production.
|
|
| 5. |
- Teare, Harriet J.A., et al.
(author)
-
The governance structure for data access in the DIRECT consortium : An innovative medicines initiative (IMI) project
- 2018
-
In: Life Sciences, Society and Policy. - : Springer Science and Business Media LLC. - 2195-7819. ; 14:1
-
Journal article (peer-reviewed)abstract
- Biomedical research projects involving multiple partners from public and private sectors require coherent internal governance mechanisms to engender good working relationships. The DIRECT project is an example of such a venture, funded by the Innovative Medicines Initiative Joint Undertaking (IMI JU). This paper describes the data access policy that was developed within DIRECT to support data access and sharing, via the establishment of a 3-tiered Data Access Committee. The process was intended to allow quick access to data, whilst enabling strong oversight of how data were being accessed and by whom, and any subsequent analyses, to contribute to the overall objectives of the consortium.
|
|
| 6. |
- Kildegaard, Kanchana R., et al.
(author)
-
Evolution reveals a glutathione-dependent mechanism of 3-hydroxypropionic acid tolerance
- 2014
-
In: Metabolic engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 26, s. 57-66
-
Journal article (peer-reviewed)abstract
- Biologically produced 3-hydroxypropionic acid (3HP) is a potential source for sustainable acrylates and can also find direct use as monomer in the production of biodegradable polymers. For industrial scale production there is a need for robust cell factories tolerant to high concentration of 3HP, preferably at low pH. Through adaptive laboratory evolution we selected S. cerevisiae strains with improved tolerance to 3HP at pH 3.5. Genome sequencing followed by functional analysis identified the causal mutation in SFA1 gene encoding S-(hyclroxymerhyl)glutathione dehydrogenase. Based on our findings, we propose that 3HP toxicity is mediated by 3-hydroxypropionic aldehyde (reuterin ) and that glutathione-dependent reactions are used for reuterin detoxification. The identified molecular response to 3HP and reuterin may well be a general mechanism for handling resistance to organic acid and aldehydes by living cells. (C) 2014 International Metabolic Engineering Society Published by Elsevier Inc. On behalf of International Metabolic Engineering Society. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/)
|
|
| 7. |
- Koivula, Robert, et al.
(author)
-
Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes : rationale and design of the epidemiological studies within the IMI DIRECT Consortium
- 2014
-
In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 57:6, s. 1132-1142
-
Journal article (peer-reviewed)abstract
- AIMS/HYPOTHESIS:The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT.METHODS:Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size ~1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MRI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires.CONCLUSIONS/INTERPRETATION:DIRECT will yield an unprecedented array of biomaterials and data. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes
|
|
| 8. |
- Pereira, Rui, 1986, et al.
(author)
-
Adaptive laboratory evolution of tolerance to dicarboxylic acids in Saccharomyces cerevisiae
- 2019
-
In: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 56, s. 130-141
-
Journal article (peer-reviewed)abstract
- Improving the growth phenotypes of microbes in high product concentrations is an essential design objective in the development of robust cell factories. However, the limited knowledge regarding tolerance mechanisms makes rational design of such traits complicated. Here, adaptive laboratory evolution was used to explore the tolerance mechanisms that Saccharomyces cerevisiae can evolve in the presence of inhibiting concentrations of three dicarboxylic acids: glutaric acid, adipic acid and pimelic acid. Whole-genome sequencing of tolerant mutants enabled the discovery of the genetic changes behind tolerance and most mutations could be linked to the up-regulation of multidrug resistance transporters. The amplification of QDR3, in particular, was shown to confer tolerance not only to the three dicarboxylic acids investigated, but also towards muconic acid and glutaconic acid. In addition to increased acid tolerance, QDR3 overexpression also improved the production of muconic acid in the context of a strain engineered for producing this compound.
|
|
| 9. |
- Pereira, Rui, 1986, et al.
(author)
-
Elucidating aromatic acid tolerance at low pH in Saccharomyces cerevisiae using adaptive laboratory evolution
- 2020
-
In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 117:45, s. 27954-27961
-
Journal article (peer-reviewed)abstract
- Toxicity from the external presence or internal production of compounds can reduce the growth and viability of microbial cell factories and compromise productivity. Aromatic compounds are generally toxic for microorganisms, which makes their production in microbial hosts challenging. Here we use adaptive laboratory evolution to generate Saccharomyces cerevisiae mutants tolerant to two aromatic acids, coumaric acid and ferulic acid. The evolution experiments were performed at low pH (3.5) to reproduce conditions typical of industrial processes. Mutant strains tolerant to levels of aromatic acids near the solubility limit were then analyzed by whole genome sequencing, which revealed prevalent point mutations in a transcriptional activator (Aro80) that is responsible for regulating the use of aromatic amino acids as the nitrogen source. Among the genes regulated by Aro80, ESBP6 was found to be responsible for increasing tolerance to aromatic acids by exporting them out of the cell. Further examination of the native function of Esbp6 revealed that this transporter can excrete fusel acids (byproducts of aromatic amino acid catabolism) and this role is shared with at least one additional transporter native to S. cerevisiae (Pdr12). Besides conferring tolerance to aromatic acids, ESBP6 overexpression was also shown to significantly improve the secretion in coumaric acid production strains. Overall, we showed that regulating the activity of transporters is a major mechanism to improve tolerance to aromatic acids. These findings can be used to modulate the intracellular concentration of aromatic compounds to optimize the excretion of such products while keeping precursor molecules inside the cell.
|
|
| 10. |
- Limeta, Angelo, 1996, et al.
(author)
-
Leveraging high-resolution omics data for predicting responses and adverse events to immune checkpoint inhibitors
- 2023
-
In: Computational and Structural Biotechnology Journal. - 2001-0370. ; 21, s. 3912-3919
-
Research review (peer-reviewed)abstract
- A long-standing goal of personalized and precision medicine is to enable accurate prediction of the outcomes of a given treatment regimen for patients harboring a disease. Currently, many clinical trials fail to meet their endpoints due to underlying factors in the patient population that contribute to either poor responses to the drug of interest or to treatment-related adverse events. Identifying these factors beforehand and correcting for them can lead to an increased success of clinical trials. Comprehensive and large-scale data gathering efforts in biomedicine by omics profiling of the healthy and diseased individuals has led to a treasure-trove of host, disease and environmental factors that contribute to the effectiveness of drugs aiming to treat disease. With increasing omics data, artificial intelligence allows an in-depth analysis of big data and offers a wide range of applications for real-world clinical use, including improved patient selection and identification of actionable targets for companion therapeutics for improved translatability across more patients. As a blueprint for complex drug-disease-host interactions, we here discuss the challenges of utilizing omics data for predicting responses and adverse events in cancer immunotherapy with immune checkpoint inhibitors (ICIs). The omics-based methodologies for improving patient outcomes as in the ICI case have also been applied across a wide-range of complex disease settings, exemplifying the use of omics for in-depth disease profiling and clinical use.
|
|
