| 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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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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| 3. |
- Thörn, Christian, 1983, et al.
(författare)
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Immobilization of feruloyl esterases in mesoporous silica
- 2011
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Ingår i: Frontiers of silica research,15-16 March, Chalmers University of Technology, Göteborg, Sweden.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Mesoporous silica materials have become popular as immobilization support for enzymes due to advantages such as high protein loading capacity and enhanced enzyme activity because of confinement into pores. Immobilization of enzymes is often required for sufficient enzyme stability and to enable recovery in industrially feasible and efficient processes. Feruloyl esterases is a class of enzymes used in biocatalysis for refinement of hydroxycinnamic acids. These compounds have shown to have antioxidant and antibacterial properties, though modification of solubility is necessary for the compounds to be of interest in different commercial products. Previous work has showed that mesoporous silica is a robust immobilization support for feruloyl esterases and that transesterification activity was favored over hydrolysis. Immobilization of feruloyl esterases (FoFAEC) in SBA-15 mesoporous silica showed to be highly affected by pH. Testing the immobilized enzymes for transesterification of methyl ferulate to butyl ferulate showed that the specific activity was affected by the pH at which the enzymes had been immobilized. Consequently there is a pH memory effect, which could be reverted by subsequent washing with a buffer of different pH. The current work involves testing a pH probe bound to the enzyme which will give information of the microenvironment pH close to the enzyme. Additionally, an in silico model of FoFAEC has been developed so that the dimensions of the enzyme can be related to the pore size. The model will also be used to simulate the enzyme structure at different pH, predict orientation and adsorption behavior. The aim is to understand how mesoporous materials can be used to alter the enzymatic activity upon immobilization and in the end develop improved feruloyl esterase biocatalysts that allow customization of the antioxidant properties of hydroxycinnamic acids.
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| 4. |
- Thörn, Christian, 1983, et al.
(författare)
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Understanding the pH-dependent immobilization efficacy of feruloyl esterase-C on mesoporous silica and its structure activity changes
- 2013
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Ingår i: Journal of Molecular Catalysis - B Enzymatic. - : Elsevier BV. - 1381-1177 .- 1873-3158. ; 93, s. 65-72
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of the present investigation was to study the pH dependence of both the immobilization process and the enzyme activity of a feruloyl esterase (FoFaeC from Fusarium oxysporum) immobilized in mesoporous silica. This was done by interpreting experimental results with theoretical molecular modeling of the enzyme structure. Modeling of the 3D structure of the enzyme together with calculations of the electrostatic surface potential showed that changes in the electrostatic potential of the protein surface were correlated with the pH dependence of the immobilization process. High immobilization yields were associated with an increase in pH. The transesterification activity of both immobilized and free enzyme was studied at different values of pH and the optimal pH of the immobilized enzyme was found to be one unit lower than that for the free enzyme. The surface charge distribution around the binding pocket was identified as being a crucial factor for the accessibility of the active site of the immobilized enzyme, indicating that the orientation of the enzyme inside the pores is pH dependent. Interestingly, it was observed that the immobilization pH affects the specific activity, irrespective of the changes in reaction pH. This was identified as a pH memory effect for the immobilized enzyme. On the other hand, a change in product selectivity of the immobilized enzyme was also observed when the transesterification reaction was run in MOPS buffer instead of citrate phosphate buffer. Molecular docking studies revealed that the MOPS buffer molecule can bind to the enzyme binding pocket, and can therefore be assumed to modulate the product selectivity of the immobilized enzyme toward transesterification.
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| 5. |
- Udatha, Gupta, 1984, et al.
(författare)
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Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae
- 2012
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 7:6, s. e39473-
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Tidskriftsartikel (refereegranskat)abstract
- Background:Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed.Methodology/Principal Findings: The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations.Conclusions/Significance:Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods.
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| 6. |
- Udatha, Gupta, 1984, et al.
(författare)
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Deciphering the signaling mechanisms of the plant cell wall degradation machinery in Aspergillus oryzae
- 2015
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Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 9:1, s. 20-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The gene expression and secretion of fungal lignocellulolytic enzymes are tightly controlled at the transcription level using independent mechanisms to respond to distinct inducers from plant biomass. An advanced systems-level understanding of transcriptional regulatory networks is required to rationally engineer filamentous fungi for more efficient bioconversion of different types of biomass. Results: In this study we focused on ten chemically defined inducers to drive expression of cellulases, hemicellulases and accessory enzymes in the model filamentous fungus Aspergillus oryzae and shed light on the complex network of transcriptional activators required. The chemical diversity analysis of the inducers, based on 186 chemical descriptors calculated from the structure, resulted into three clusters, however, the global, metabolic and extracellular protein transcription of the A. oryzae genome were only partially explained by the chemical similarity of the enzyme inducers. Genes encoding enzymes that have attracted considerable interest such as cellobiose dehydrogenases and copper-dependent polysaccharide mono-oxygenases presented a substrate-specific induction. Several homology-model structures were derived using ab-initio multiple threading alignment in our effort to elucidate the interplay of transcription factors involved in regulating plant-deconstructing enzymes and metabolites. Systematic investigation of metabolite-protein interactions, using the 814 unique reactants involved in 2360 reactions in the genome scale metabolic network of A. oryzae, was performed through a two-step molecular docking against the binding pockets of the transcription factors AoXlnR and AoAmyR. A total of six metabolites viz., sulfite (H2SO3), sulfate (SLF), uroporphyrinogen III (UPGIII), ethanolamine phosphate (PETHM), D-glyceraldehyde 3-phosphate (T3P1) and taurine (TAUR) were found as strong binders, whereas the genes involved in the metabolic reactions that these metabolites appear were found to be significantly differentially expressed when comparing the inducers with glucose. Conclusions: Based on our observations, we believe that specific binding of sulfite to the regulator of the cellulase gene expression, AoXlnR, may be the molecular basis for the connection of sulfur metabolism and cellulase gene expression in filamentous fungi. Further characterization and manipulation of the regulatory network components identified in this study, will enable rational engineering of industrial strains for improved production of the sophisticated set of enzymes necessary to break-down chemically divergent plant biomass.
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| 7. |
- Udatha, Gupta, 1984, et al.
(författare)
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Descriptor-based computational analysis and molecular simulation studies reveals a novel classification scheme and structure-function relationship elements for feruloyl esterases
- 2011
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Ingår i: Enzyme Engineering XXI, Vail, Colorado, USA. ; 18th -22nd September, 2011
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- One of the most intriguing groups of enzymes, the feruloyl esterases (FAEs), is ubiquitous in both simple and complex organisms. FAEs have gained importance in biofuel, medicine and food industries due to their capability of acting on a large range of substrates for cleaving ester bonds and synthesizing high-added value molecules through esterification and transesterification reactions. During the past two decades extensive studies have been carried out on the production and partial characterization of FAEs from fungi, while much less is known about FAEs of bacterial or plant origin. Initial classification studies on FAEs were restricted on sequence similarity and substrate specificity on just four model substrates and considered only a handful of FAEs belonging to the fungal kingdom. Our study centers on the descriptor-based classification and structural analysis of experimentally verified and putative FAEs. Support Vector Machine model was constructed for the classification of 365 FAEs into the pre-assigned clusters and the model successfully recognized 98.2% of the training sequences and all the sequences of the blind test. The underlying functionality of the 12 proposed FAE families was validated against a combination of prediction tools and published experimental data. Another important aspect of the present work involves the development of pharmacophore models for the new FAE families, for which sufficient information on known substrates existed. The development of pharmacophore models for specific FAE sub-families will have a huge impact on the application of members of the particular group to completely novel and unexpected substrates. Virtual screening with the developed pharmacophores of chemical and natural compound databases could reveal unique opportunities for FAEs-based-biocatalytic modifications to synthesize compounds with altered or improved medicinal properties. We expressed three enzymes representing different novel FEF families in Pichia pastoris and probed their specificity profiles. Structural and functional features of expressed FEF members were probed using Circular dichroism (CD) spectroscopy and Molecular simulations were done to understand the structural-function relationships of the FAEs for engineering studies. The active site residues were detected for the three expressed FAEs based on titration curves of amino acid residues as a function of pH obtained through simulation systems. We are confident that the classification and characterization of this expanding super family of enzymes will provide researchers and industries with the toolbox from which to select FAEs for suitable reactions and applications; nevertheless, the framework presented here is applicable to every poorly characterized enzyme family and understanding their structure-function relationships.
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| 8. |
- Udatha, Gupta, 1984, et al.
(författare)
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Descriptor-based computational analysis reveals a new classification scheme for feruloyl esterase
- 2010
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Ingår i: 10th Swedish Bioinformatics Workshop, Gothenburg, Sweden. ; March 4-5, 2010
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- One of the most important groups of enzymes, the feruloyl esterases (FAEs), is ubiquitous in both simple and complex organisms. FAEs have gained importance in biofuel, medicine, food and nutrition industries due to their capability of acting on a large range of substrates for cleaving or/and synthesizing ester bonds. Despite the extensive studies in the past two decades on the production and partial characterization of FAEs there is poor knowledge on the control mechanisms of substrate recognition.The present work centers on the descriptor-based characterization and structural analysis of FAEs to propose a complete classification system of this industrially important enzyme. We collected 365 sequences from plants, fungi and bacteria and clustered them based on 91 descriptors derived from the amino acid sequence. A Support Vector Machine (SVM) model was subsequently trained for the classification of the sequences, which led to the identification of ten different sub families. The SVM model successfully recognized 98.30% of the sequences correctly that belong to respective clusters and all the sequences of the blind test set. Another important aspect of the present work involved the structural analysis of previously characterized FAEs based on the pharmacophoric features of the known substrates. In this work we apply an array of computational tools and we succeed to develop a new classification scheme for FAEs which opens new vistas in the application of this intriguing group of enzymes in biocatalytic transformations. The present work is not restricted to FAEs but represents a framework for the functional characterization and identification of substrate specificity for any poorly characterized enzyme group. In addition we demonstrated that sequence information can be used for constructing models that reveal the underlying structural reasons determining substrate specificities.
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| 9. |
- Udatha, Gupta, 1984, et al.
(författare)
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Descriptor-based computational analysis reveals a novel classification scheme for feruloyl esterase enzyme families
- 2011
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Ingår i: International Conference on Bioinformatics, Kuala Lumpur, Malaysia. ; 20th November – 2nd December, 2011
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundOne of the most intriguing groups of enzymes, the feruloyl esterases (FAEs), is ubiquitous in both simple and complex organisms. FAEs have gained importance in biofuel, medicine and food industries due to their capability of acting on a large range of substrates for cleaving ester bonds and synthesizing high-added value molecules through esterification and transesterification reactions. During the past two decades extensive studies have been carried out on the production and partial characterization of FAEs from fungi, while much less is known about FAEs of bacterial or plant origin. Initial classification studies on FAEs were restricted on sequence similarity and substrate specificity on just four model substrates and considered only a handful of FAEs belonging to the fungal kingdom.ResultsOur study centers on the descriptor-based classification and structural analysis of experimentally verified and putative FAEs. 365 FAE-related sequences of fungal, bacterial and plantae origin were collected and they were clustered using Self Organizing Maps followed by k-means clustering into distinct groups based on amino acid composition and physico-chemical composition descriptors derived from the respective amino acid sequence. Support Vector Machine model was constructed for the classification of 365 FAEs into the pre-assigned clusters and the model successfully recognized 98.2% of the training sequences and all the sequences of the blind test. The underlying functionality of the 12 proposed FAE families was validated against a combination of prediction tools and published experimental data. Another important aspect of the present work involves the development of pharmacophore models for the new FAE families, for which sufficient information on known substrates existed. ConclusionsThe development of pharmacophore models for specific FAE sub-families will have a huge impact on the application of members of the particular group to completely novel and unexpected substrates. Virtual screening with the developed pharmacophores of chemical and natural compound databases could reveal unique opportunities for FAEs-based-biocatalytic modifications to synthesize compounds with altered or improved medicinal properties. We are confident that the classification and characterization of this expanding super family of enzymes will provide researchers and industries with the toolbox from which to select FAEs for suitable reactions and applications; nevertheless, the framework presented here is applicable to every poorly characterized enzyme family and understanding their structure-function relationships. We welcome interested researchers to submit putative FAE sequences to us for sub-grouping as per the new classification system. Sequences can be submitted at http://faeclassification.webs.com/
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| 10. |
- Udatha, Gupta, 1984, et al.
(författare)
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How well do the substrates KISS the enzyme? Molecular docking program selection for feruloyl esterases
- 2012
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 2, s. Article number: 323-
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Tidskriftsartikel (refereegranskat)abstract
- Molecular docking is the most commonly used technique in the modern drug discovery process where computational approaches involving docking algorithms are used to dock small molecules into macromolecular target structures. Over the recent years several evaluation studies have been reported by independent scientists comparing the performance of the docking programs by using default ‘black box’ protocols supplied by the software companies. Such studies have to be considered carefully as the docking programs can be tweaked towards optimum performance by selecting the parameters suitable for the target of interest. In this study we address the problem of selecting an appropriate docking and scoring function combination (88 docking algorithm-scoring functions) for substrate specificity predictions for feruloyl esterases, an industrially relevant enzyme family. We also propose the ‘Key Interaction Score System’ (KISS), a more biochemically meaningful measure for evaluation of docking programs based on pose prediction accuracy.
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