| 1. |
- Wortman, J. R., et al.
(författare)
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The 2008 update of the Aspergillus nidulans genome annotation: A community effort
- 2009
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Ingår i: Fungal Genetics and Biology. - : Elsevier BV. - 1096-0937 .- 1087-1845. ; 46, s. S2-S13
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Tidskriftsartikel (refereegranskat)abstract
- The identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology. (C) 2009 Elsevier Inc. All rights reserved.
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| 2. |
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| 3. |
- Cimini, D., et al.
(författare)
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Global transcriptional response of Saccharomyces cerevisiae to the deletion of SDH3
- 2009
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Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 3, s. 17 (artno)-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Mitochondrial respiration is an important and widely conserved cellular function in eukaryotic cells. The succinate dehydrogenase complex (Sdhp) plays an important role in respiration as it connects the mitochondrial respiratory chain to the tricarboxylic acid (TCA) cycle where it catalyzes the oxidation of succinate to fumarate. Cellular response to the Sdhp dysfunction (i.e. impaired respiration) thus has important implications not only for biotechnological applications but also for understanding cellular physiology underlying metabolic diseases such as diabetes. We therefore explored the physiological and transcriptional response of Saccharomyces cerevisiae to the deletion of SDH3, that codes for an essential subunit of the Sdhp. Results: Although the Sdhp has no direct role in transcriptional regulation and the flux through the corresponding reaction under the studied conditions is very low, deletion of SDH3 resulted in significant changes in the expression of several genes involved in various cellular processes ranging from metabolism to the cell-cycle. By using various bioinformatics tools we explored the organization of these transcriptional changes in the metabolic and other cellular functional interaction networks. Conclusion: Our results show that the transcriptional regulatory response resulting from the impaired respiratory function is linked to several different parts of the metabolism, including fatty acid and sterol metabolism.
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| 4. |
- Fazio, Allessandro, et al.
(författare)
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Transcription factor control of growth rate dependent genes in Saccharomyces cerevisiae: A three factor design
- 2008
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Ingår i: BMC Genomics. ; 9:341
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Tidskriftsartikel (refereegranskat)abstract
- Background: Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostate cultures of Saccharomyces cerevisiae. The three factors we considered were specific growth rate, nutrient limitation, and oxygen availability.Results: We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which mRNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed de novo synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known transcription factor target sets, transcription factors that coordinate balanced growth were also identified. Our analysis shows that Fhl I, Rap I, and Sfp I, regulating protein biosynthesis, have significantly enriched target sets for genes up-regulated with increasing growth rate. Cell cycle regulators, such as Ace2 and Swi6, and stress response regulators, such as Yap I, were also shown to have significantly enriched target sets.Conclusion: Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more conservative estimate of growth rate dependent genes than previously reported. We also provide a global view of how a small set of transcription factors, 13 in total, contribute to control of cellular growth rate. We anticipate that multi-factorial designs will play an increasing role in elucidating cellular regulation.
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| 5. |
- Moxley, J.F., et al.
(författare)
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Linking transcriptional regulation and high resolution metabolic fluxes in yeast modulated by the global regulator Gcn4p
- 2009
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 106:16, s. 6477-6482
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Tidskriftsartikel (refereegranskat)abstract
- Genome sequencing dramatically increased our ability to understand cellular response to perturbation. Integrating system-wide measurements such as gene expression with networks of protein protein interactions and transcription factor binding revealed critical insights into cellular behavior. However, the potential of systems biology approaches is limited by difficulties in integrating metabolic measurements across the functional levels of the cell despite their being most closely linked to cellular phenotype. To address this limitation, we developed a model-based approach to correlate mRNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental (13)C-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator Gcn4p. Although mRNA expression alone did not directly predict metabolic response, this correlation improved through incorporating a network-based model of amino acid biosynthesis (from r = 0.07 to 0.80 for mRNA-flux agreement). The model provides evidence of general biological principles: rewiring of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow-on transcriptional regulators that were experimentally validated with additional (13)C-based flux measurements. As a first step in linking metabolic control and genetic regulatory networks, this model underscores the importance of integrating diverse data types in large-scale cellular models. We anticipate that an integrated approach focusing on metabolic measurements will facilitate construction of more realistic models of cellular regulation for understanding diseases and constructing strains for industrial applications.
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| 6. |
- Nielsen, Jens, 1963, et al.
(författare)
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Multi-disciplinary optimization of railway wheels
- 2006
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Ingår i: Journal of Sound and Vibration. - : Elsevier BV. - 1095-8568 .- 0022-460X. ; 293:3-5, s. 510-521
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Tidskriftsartikel (refereegranskat)abstract
- A numerical procedure for multi-disciplinary optimization of railway wheels, based on Design of Experiments (DOE) methodology and automated design, is presented. The target is a wheel design that meets the requirements for fatigue strength, while minimizing the unsprung mass and rolling noise. A 3-level full factorial (3LFF) DOE is used to collect data points required to set up Response Surface Models (RSM) relating design and response variables in the design space. Computationally efficient simulations are thereafter performed using the RSM to identify the solution that best fits the design target. A demonstration example, including four geometric design variables in a parametric finite element (FE) model, is presented. The design variables are wheel radius, web thickness, lateral offset between rim and hub, and radii at the transitions rim/web and hub/web, but more variables (including material properties) can be added if needed. To improve further the performance of the wheel design, a constrained layer damping (CLD) treatment is applied on the web. For a given load case, compared to a reference wheel design without CLD, a combination of wheel shape and damping optimization leads to the conclusion that a reduction in the wheel component of A-weighted rolling noise of 11 dB can be achieved if a simultaneous increase in wheel mass of 14 kg is accepted.
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| 7. |
- Nookaew, Intawat, 1977, et al.
(författare)
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The genome-scale metabolic model ilN800 of Saccharomyces cerevisiae and its validation: a scaffold to query lipid metabolism
- 2008
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Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 2:71
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Tidskriftsartikel (refereegranskat)abstract
- Background: Up to now, there have been three published versions of a yeast genome-scale metabolic model: iFF708, iND750 and iLL672. All three models, however, lack a detailed description of lipid metabolism and thus are unable to be used as integrated scaffolds for gaining insights into lipid metabolism from multilevel omic measurement technologies (e.g. genome-wide mRNA levels). To overcome this limitation, we reconstructed a new version of the Saccharomyces cerevisiae genome-scale model, ilN800 that includes a more rigorous and detailed descrition of lipid metabolism. Results: The reconstructed metabolic model comprises 1446 reactions and 1013 metabolites. Beyond incorporating new reactions involved in lipid metabolism, we also present new biomass equations that improve the predictive power of flux balance analysis simulations. Predictions of both growth capability and large scale in silico single gene deletions by ilN800 were consistent with experimental data. In addition, 13C-labeling experiments validated the new biomass equations and calculated intracellular fluxes. To demonstrate the applicability of ilN800, we show that the model can be used as a scaffold to reveal the regulatory importance of lipid metabolism precursors and intermediates that would have been missed in previous models from transcriptome datasets. Conclusions: Performing integrated analyses using ilN800 as a network scaffold is shown to be a valuable tool for elucidating the behavior of complex metabolic networks, particularly for identifying regulatory targets in lipid metabolism that can be used for industrial applications or for understanding lipid disease states.
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| 8. |
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| 9. |
- Rocha, M., et al.
(författare)
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Natural computation meta-heuristics for the in silico optimization of microbial strains
- 2008
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 9, s. 499-
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Tidskriftsartikel (refereegranskat)abstract
- Background: One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/ productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for in silico metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution. Results: This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of in silico metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using S. cerevisiae and E. coli as model organisms. The proposed algorithms are able to reach optimal/ near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs. Conclusion: The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automati c discovery of the approximate number of gene deletions, without compromising the optimality of the solutions. © 2008 Rocha et al; licensee BioMed Central Ltd.
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| 10. |
- Usaite, Renata, et al.
(författare)
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Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator
- 2009
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 5:319, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Highly conserved among eukaryotic cells, ghe AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite levels in wild type, ∆snf1, ∆snf4, and ∆snf1∆snf4 knockout strains. Using four newly developed computional tools, including novel DOGMA sub-network analysis, we showed the benefits of three-level ome-data integration to uncover the global Snf1 kinase role in yeast. We for the first time identified Snf1's global regulation on gene and protein expression levels, and showed that yeast Snf1 has a far more extensive function in controlling energy metabolism that reported earlier. Additionally, we identified complementary roles of Snf1 and Snf4. Similar to the function of AMPK in humans, our findings showed that Snf1 is a low-energy checkpoint and that yeast can be used more extensively as a model system for studying the molecular mechanisms underlying the global regulation of AMPK in mammals, failure of which leads to metabolic diseases.
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