| 1. |
- Canelas, A.B., et al.
(författare)
-
Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains
- 2010
-
Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 1:9
-
Tidskriftsartikel (refereegranskat)abstract
- The field of systems biology is often held back by difficulties in obtaining comprehensive, high-quality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. On the basis of the integrated analysis of the high-throughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism.
|
|
| 2. |
- Chumnanpuen, Pramote, 1983, et al.
(författare)
-
Dynamic Metabolic Footprinting Reveals the Key Components of Metabolic Network in Yeast Saccharomyces cerevisiae
- 2014
-
Ingår i: International Journal of Genomics. - : Hindawi Limited. - 2314-436X .- 2314-4378. ; 2014, s. Art. no. 894296-
-
Tidskriftsartikel (refereegranskat)abstract
- Metabolic footprinting offers a relatively easy approach to exploit the potentials of metabolomics for phenotypic characterization of microbial cells. To capture the highly dynamic nature of metabolites, we propose the use of dynamic metabolic footprinting instead of the traditional method which relies on analysis at a single time point. Using direct infusion-mass spectrometry (DI-MS), we could observe the dynamic metabolic footprinting in yeast S. cerevisiae BY4709 (wild type) cultured on 3 different C-sources (glucose, glycerol, and ethanol) and sampled along 10 time points with 5 biological replicates. In order to analyze the dynamic mass spectrometry data, we developed the novel analysis methods that allow us to perform correlation analysis to identify metabolites that significantly correlate over time during growth on the different carbon sources. Both positive and negative electrospray ionization (ESI) modes were performed to obtain the complete information about the metabolite content. Using sparse principal component analysis (Sparse PCA), we further identified those pairs of metabolites that significantly contribute to the separation. From the list of significant metabolite pairs, we reconstructed an interaction map that provides information of how different metabolic pathways have correlated patterns during growth on the different carbon sources.
|
|
| 3. |
- Chumnanpuen, Pramote, 1983, et al.
(författare)
-
Integrated analysis of transcriptome and lipid profiling reveals the co-influences of inositol-choline and Snf1 in controlling lipid biosynthesis in yeast
- 2012
-
Ingår i: Molecular Genetics and Genomics. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 287:7, s. 541-554
-
Tidskriftsartikel (refereegranskat)abstract
- In the yeast Saccharomyces cerevisiae many genes involved in lipid biosynthesis are transcriptionally controlled by inositol-choline and the protein kinase Snf1. Here we undertook a global study on how inositol-choline and Snf1 interact in controlling lipid metabolism in yeast. Using both a reference strain (CEN.PK113-7D) and a snf1 Delta strain cultured at different nutrient limitations (carbon and nitrogen), at a fixed specific growth rate of 0.1 h(-1), and at different inositol choline concentrations, we quantified the expression of genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through integrated analysis of the transcriptome, the lipid profiling and the fluxome, it was possible to obtain a high quality, large-scale dataset that could be used to identify correlations and associations between the different components. At the transcription level, Snf1 and inositol-choline interact either directly through the main phospholipid-involving transcription factors (i.e. Ino2, Ino4, and Opi1) or through other transcription factors e.g. Gis1, Mga2, and Hac1. However, there seems to be flux regulation at the enzyme levels of several lipid involving enzymes. The analysis showed the strength of using both transcriptome and lipid profiling analysis for mapping the co-influence of inositol-choline and Snf1 on phospholipid metabolism.
|
|
| 4. |
- Chumnanpuen, Pramote, 1983, et al.
(författare)
-
Integrated analysis, transcriptome-lipidome, reveals the effects of INO-level (INO2 and INO4) on lipid metabolism in yeast
- 2013
-
Ingår i: BMC Systems Biology. - 1752-0509. ; 7 (Suppl 3):S7
-
Tidskriftsartikel (refereegranskat)abstract
- In the yeast Saccharomyces cerevisiae, genes containing UASINO sequences are regulated by the Ino2/Ino4 and Opi1 transcription factors, and this regulation controls lipid biosynthesis. The expression level of INO2 and INO4 genes (INO-level) at different nutrient limited conditions might lead to various responses in yeast lipid metabolism.In this study, we undertook a global study on how INO-levels (transcription level of INO2 and INO4) affect lipid metabolism in yeast and we also studied the effects of single and double deletions of the two INO-genes (deficient effect). Using 2 types of nutrient limitations (carbon and nitrogen) in chemostat cultures operated at a fixed specific growth rate of 0.1 h-1 and strains having different INO-level, we were able to see the effect on expression level of the genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through combined measurements of the transcriptome, metabolome, and lipidome it was possible to obtain a large dataset that could be used to identify how the INO-level controls lipid metabolism and also establish correlations between the different components.In this study, we undertook a global study on how INO-levels (transcription level of INO2 and INO4) affect lipid metabolism in yeast and we also studied the effects of single and double deletions of the two INO-genes (deficient effect). Using 2 types of nutrient limitations (carbon and nitrogen) in chemostat cultures operated at a fixed specific growth rate of 0.1 h-1 and strains having different INO-level, we were able to see the effect on expression level of the genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through combined measurements of the transcriptome, metabolome, and lipidome it was possible to obtain a large dataset that could be used to identify how the INO-level controls lipid metabolism and also establish correlations between the different components.Our analysis showed the strength of using a combination of transcriptome and lipidome analysis to illustrate the effect of INO-levels on phospholipid metabolism and based on our analysis we established a global regulatory map.
|
|
| 5. |
- Chumnanpuen, Pramote, 1983, et al.
(författare)
-
Lipid biosynthesis monitored at the single-cell level in Saccharomyces cerevisiae
- 2012
-
Ingår i: Biotechnology journal. - : Wiley. - 1860-6768 .- 1860-7314. ; 7:5, s. 594-601
-
Tidskriftsartikel (refereegranskat)abstract
- There is increasing interest in bioengineering of lipids for use in functional foods, pharmaceuticals, and biofuels. Saccharomyces cerevisiae is a widely utilized cell factory for biotechnological production, thus a tempting alternative. Herein, we show how its neutral lipid accumulation varies throughout metabolic phases under nutritional conditions relevant for large-scale fermentation. Population-averaged metabolic data were correlated with lipid storage at the single-cell level monitored at submicron resolution by label-free coherent anti-Stokes Raman scattering (CARS) microscopy. While lipid droplet sizes are fairly constant, the number of droplets is a dynamic parameter determined by glucose and ethanol levels. The lowest number of lipid droplets is observed in the transition phase between glucose and ethanol fermentation. It is followed by a buildup during the ethanol phase. The surplus of accumulated lipids is then mobilized at concurrent glucose and ethanol starvation in the subsequent stationary phase. Thus, the highest amount of lipids is found in the ethanol phase, which is about 0.3 fL/cell. Our results indicate that the budding yeast, S. cerevisiae, can be used for the biosynthesis of lipids and demonstrate the strength of CARS microscopy for monitoring the dynamics of lipid metabolism at the single-cell level of importance for optimized lipid production.
|
|
| 6. |
- Chumnanpuen, Pramote, 1983
(författare)
-
Systems Biology of Yeast Lipid Metabolism
- 2012
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Lipid metabolism plays an important role in the development of many different life-style related diseases, such as type 2 diabetes and atherosclerosis, and understanding the molecular mechanisms behind regulation of lipid biosynthesis and degradation may lead to development of new therapies. In this project we undertook a global study of lipid metabolism in the eukaryotic model organism Saccharomyces cerevisiae. The objective of this project is to quantify how the fluxes in lipid metabolism of eukaryotic cells are controlled by different component of the regulatory network. Using systems biology approaches there was established a global regulatory model for lipid metabolism, and it was quantified how the fluxes toward different lipid components are regulated. Using different mutants that carry deletion in genes encoding key transcriptional factors and protein kinases involved in lipid regulation, the fluxes towards the different lipid components was perturbed. The wild-type yeast strain CEN.PK113-7D and the yeast mutants opi1∆, snf1∆, tor1∆, ino2∆, ino4∆, and ino2∆ino4∆ were grown in chemostat cultures at carbon or nitrogen-limited conditions and also high or low inositol-choline (IC) condition at a dilution rate of 0.1 h-1. At steady state conditions samples were withdrawn for analysis of the transcriptome, the metabolome and the lipidome. There was also developed 3 high-throughput methods for lipid quantification, i) for storage lipid monitoring at single-cell level using CARS microscopy, ii) for lipid classes analysis based on microwave-assisted extraction, HPLC-CAD, and iii) for fatty acids species analysis based on microwave-assisted derivatization. Through combined measurements of the transcriptome, the metabolome, the lipidome and the fluxome it was possible to obtain a large dataset that could be used to identify correlations between the different components such as the co-influences of Snf1-IC effects, INO-level, and Snf1-TORC1 effects on yeast lipid metabolism.
|
|
| 7. |
- Khoomrung, Sakda, 1978, et al.
(författare)
-
Fast and accurate preparation fatty acid methyl esters by microwave-assisted derivatization in the yeast Saccharomyces cerevisiae
- 2012
-
Ingår i: Applied Microbiology and Biotechnology. - : Springer Science and Business Media LLC. - 1432-0614 .- 0175-7598. ; 94:6, s. 1637-1646
-
Tidskriftsartikel (refereegranskat)abstract
- We present a fast and accurate method for preparation of fatty acid methyl esters (FAMEs) using microwave-assisted derivatization of fatty acids present in yeast samples. The esterification of free/bound fatty acids to FAMEs was completed within 5 min, which is 24 times faster than with conventional heating methods. The developed method was validated in two ways: (1) through comparison with a conventional method (hot plate) and (2) through validation with the standard reference material (SRM) 3275-2 omega-3 and omega-6 fatty acids in fish oil (from the Nation Institute of Standards and Technology, USA). There were no significant differences (P > 0.05) in yields of FAMEs with both validations. By performing a simple modification of closed-vessel microwave heating, it was possible to carry out the esterification in Pyrex glass tubes kept inside the closed vessel. Hereby, we are able to increase the number of sample preparations to several hundred samples per day as the time for preparation of reused vessels was eliminated. Pretreated cell disruption steps are not required, since the direct FAME preparation provides equally quantitative results. The new microwave-assisted derivatization method facilitates the preparation of FAMEs directly from yeast cells, but the method is likely to also be applicable for other biological samples.
|
|
| 8. |
- Khoomrung, Sakda, 1978, et al.
(författare)
-
Rapid Quantification of Yeast Lipid using Microwave-Assisted Total Lipid Extraction and HPLC-CAD
- 2013
-
Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 85:10, s. 4912-4919
-
Tidskriftsartikel (refereegranskat)abstract
- We here present simple and rapid methods for fast screening of yeast lipids in Saccharomyces cerevisiae. First we introduced a microwave-assisted technique for fast lipid extraction that allows the extraction of lipids within 10 min. The new method enhances extraction rate by 27 times, while maintaining product yields comparable to conventional methods (n = 14, P > 0.05). The recovery (n = 3) from spiking of synthetic standards were 92 +/- 6% for cholesterol, 95 +/- 4% for triacylglycerol, and 92 +/- 4% for free fatty acids. Additionally, the new extraction method combines cell disruption and extraction in one step, and the approach, therefore, not only greatly simplifies sample handling but also reduces analysis time and minimizes sample loss during sample preparation. Second, we developed a chromatographic separation that allowed separation of neutral and polar lipids from the extracted samples within a single run. The separation was performed based on a three gradient solvent system combined with hydrophilic interaction liquid chromatography-HPLC followed by detection using a charged aerosol detector. The method was shown to be highly reproducible in terms of retention time of the analytes (intraday; 0.002-0.034% RSD; n = 10, interday; 0.04-1.35% RSD; n = 5) and peak area (intraday; 0.63-6% RSD; n = 10, interday; 4-12% RSD; n = 5).
|
|
| 9. |
- Zhang, Jie, 1981, et al.
(författare)
-
Mapping the interaction of Snf1 with TORC1 in Saccharomyces cerevisiae
- 2011
-
Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 7
-
Tidskriftsartikel (refereegranskat)abstract
- Nutrient sensing and coordination of metabolic pathways are crucial functions for all living cells, but details of the coordination under different environmental conditions remain elusive. We therefore undertook a systems biology approach to investigate the interactions between the Snf1 and the target of rapamycin complex 1 (TORC1) in Saccharomyces cerevisiae. We show that Snf1 regulates a much broader range of biological processes compared with TORC1 under both glucose-and ammonium-limited conditions. We also find that Snf1 has a role in upregulating the NADP(+)-dependent glutamate dehydrogenase (encoded by GDH3) under derepressing condition, and therefore may also have a role in ammonium assimilation and amino-acid biosynthesis, which can be considered as a convergence of Snf1 and TORC1 pathways. In addition to the accepted role of Snf1 in regulating fatty acid (FA) metabolism, we show that TORC1 also regulates FA metabolism, likely through modulating the peroxisome and beta-oxidation. Finally, we conclude that direct interactions between Snf1 and TORC1 pathways are unlikely under nutrient-limited conditions and propose that TORC1 is repressed in a manner that is independent of Snf1.
|
|
