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Global Comparative Label-Free Yeast Proteome Analysis by LC-MS/MS After High-pH Reversed-Phase Peptide Fractionation Using Solid-Phase Extraction Cartridges. Methods Mol Biol 2021. [PMID: 34786677 DOI: 10.1007/978-1-0716-1822-6_7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
Discovery-driven comparative proteomics employing the bottom-up strategy with label-free quantification on high-resolution mass analyzers like an Orbitrap in a hybrid instrument has the capacity to reveal unique biological processes in the context of plant metabolic engineering. However, proteins are very heterogeneous in nature with a wide range of expression levels, and overall coverage may be suboptimal regarding both the number of protein identifications and sequence coverage of the identified proteins using conventional data-dependent acquisitions without sample fractionation before online nanoflow liquid chromatography-mass spectrometry (LC-MS) and tandem mass spectrometry (MS/MS). In this chapter, we detail a simple and robust method employing high-pH reversed-phase (HRP) peptide fractionation using solid-phase extraction cartridges for label-free proteomic analyses. Albeit HRP fractionation separates peptides according to their hydrophobicity like the subsequent nanoflow gradient reversed-phased LC relying on low pH mobile phase, the two methods are orthogonal. Presented here as a protocol with yeast (Saccharomyces cerevisiae) as a frequently used model organism and hydrogen peroxide to exert cellular stress and survey its impact compared to unstressed control as an example, the described workflow can be adapted to a wide range of proteome samples for applications to plant metabolic engineering research.
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Lacerda MPF, Marcelino MY, Lourencetti NMS, Neto ÁB, Gattas EA, Mendes-Giannini MJS, Fusco-Almeida AM. Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update. Curr Protein Pept Sci 2019; 20:893-906. [PMID: 31322071 DOI: 10.2174/1389203720666190715145131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 07/01/2019] [Accepted: 07/02/2019] [Indexed: 11/22/2022]
Abstract
Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.
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Affiliation(s)
- Maria Priscila F Lacerda
- Sao Paulo State University (UNESP), School of Pharmaceutical Sciences - Department of Clinical Analysis, Araraquara, Brazil
| | - Mônica Yonashiro Marcelino
- Sao Paulo State University (UNESP), School of Pharmaceutical Sciences - Department of Clinical Analysis, Araraquara, Brazil
| | - Natália M S Lourencetti
- Sao Paulo State University (UNESP), School of Pharmaceutical Sciences - Department of Clinical Analysis, Araraquara, Brazil
| | - Álvaro Baptista Neto
- Sao Paulo State University (UNESP), School of Pharmaceutical Sciences - Department of Engineering of Bioprocesses and Biotechnology, Araraquara, Brazil
| | - Edwil A Gattas
- Sao Paulo State University (UNESP), School of Pharmaceutical Sciences - Department of Engineering of Bioprocesses and Biotechnology, Araraquara, Brazil
| | | | - Ana Marisa Fusco-Almeida
- Sao Paulo State University (UNESP), School of Pharmaceutical Sciences - Department of Clinical Analysis, Araraquara, Brazil
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Li P, Fu X, Chen M, Zhang L, Li S. Proteomic profiling and integrated analysis with transcriptomic data bring new insights in the stress responses of Kluyveromyces marxianus after an arrest during high-temperature ethanol fermentation. BIOTECHNOLOGY FOR BIOFUELS 2019; 12:49. [PMID: 30899329 PMCID: PMC6408782 DOI: 10.1186/s13068-019-1390-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 02/28/2019] [Indexed: 06/01/2023]
Abstract
BACKGROUND The thermotolerant yeast Kluyveromyces marxianus is a potential candidate for high-temperature fermentation. When K. marxianus was used for high-temperature ethanol fermentation, a fermentation arrest was observed during the late fermentation stage and the stress responses have been investigated based on the integration of RNA-Seq and metabolite data. In order to bring new insights into the cellular responses of K. marxianus after the fermentation arrest during high-temperature ethanol fermentation, quantitative proteomic profiling and integrated analysis with transcriptomic data were performed in this study. RESULTS Samples collected at 14, 16, 18, 20 and 22 h during high-temperature fermentation were subjected to isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic profiling and integrated analysis with transcriptomic data. The correlations between transcripts and proteins for the comparative group 16 h vs 14 h accounted for only 4.20% quantified proteins and 3.23% differentially expressed proteins (DEPs), respectively, much higher percentages of correlations (30.56%-59.11%) were found for other comparative groups (i.e., 18 h vs 14 h, 20 h vs 14 h, and 22 h vs 14 h). According to Spearman correlation tests between transcriptome and proteome (the absolute value of a correlation coefficient between 0.5 and 1 indicates a strong correlation), poor correlations were found for all quantified proteins (R = - 0.0355 to 0.0138), DEPs (R = - 0.0079 to 0.0233) and the DEPs with opposite expression trends to corresponding differentially expressed genes (DEGs) (R = - 0.0478 to 0.0636), whereas stronger correlations were observed in terms of the DEPs with the same expression trends as the correlated DEGs (R = 0.5593 to 0.7080). The results of multiple reaction monitoring (MRM) verification indicate that the iTRAQ results were reliable. After the fermentation arrest, a number of proteins involved in transcription, translation, oxidative phosphorylation and fatty acid metabolism were down-regulated, some molecular chaperones and proteasome proteins were up-regulated, the ATPase activity significantly decreased, and the total fatty acids gradually accumulated. In addition, the contents of palmitic acid, oleic acid, C16, C18, C22 and C24 fatty acids increased by 16.77%, 28.49%, 14.14%, 26.88%, 628.57% and 125.29%, respectively. CONCLUSIONS This study confirmed some biochemical and enzymatic alterations provoked by the stress conditions in the specific case of K. marxianus: such as decreases in transcription, translation and oxidative phosphorylation, alterations in cellular fatty acid composition, and increases in the abundance of molecular chaperones and proteasome proteins. These findings provide potential targets for further metabolic engineering towards improvement of the stress tolerance in K. marxianus.
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Affiliation(s)
- Pengsong Li
- MOST-USDA Joint Research Center for Biofuels, Beijing Engineering Research Center for Biofuels, Institute of New Energy Technology, Tsinghua University, Beijing, 100084 China
| | - Xiaofen Fu
- MOST-USDA Joint Research Center for Biofuels, Beijing Engineering Research Center for Biofuels, Institute of New Energy Technology, Tsinghua University, Beijing, 100084 China
| | - Ming Chen
- MOST-USDA Joint Research Center for Biofuels, Beijing Engineering Research Center for Biofuels, Institute of New Energy Technology, Tsinghua University, Beijing, 100084 China
| | - Lei Zhang
- MOST-USDA Joint Research Center for Biofuels, Beijing Engineering Research Center for Biofuels, Institute of New Energy Technology, Tsinghua University, Beijing, 100084 China
- Agricultural Utilization Research Center, Nutrition and Health Research Institute, COFCO Corporation, No.4 Road, Future Science and Technology Park South, Beiqijia, Changping, Beijing, 102209 China
| | - Shizhong Li
- MOST-USDA Joint Research Center for Biofuels, Beijing Engineering Research Center for Biofuels, Institute of New Energy Technology, Tsinghua University, Beijing, 100084 China
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Mahipant G, Paemanee A, Roytrakul S, Kato J, Vangnai AS. The significance of proline and glutamate on butanol chaotropic stress in Bacillus subtilis 168. BIOTECHNOLOGY FOR BIOFUELS 2017; 10:122. [PMID: 28503197 PMCID: PMC5425972 DOI: 10.1186/s13068-017-0811-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Accepted: 05/04/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND Butanol is an intensively used industrial solvent and an attractive alternative biofuel, but the bioproduction suffers from its high toxicity. Among the native butanol producers and heterologous butanol-producing hosts, Bacillus subtilis 168 exhibited relatively higher butanol tolerance. Nevertheless, organic solvent tolerance mechanisms in Bacilli and Gram-positive bacteria have relatively less information. Thus, this study aimed to elucidate butanol stress responses that may involve in unique tolerance of B. subtilis 168 to butanol and other alcohol biocommodities. RESULTS Using comparative proteomics approach and molecular analysis of butanol-challenged B. subtilis 168, 108 butanol-responsive proteins were revealed, and classified into seven groups according to their biological functions. While parts of them may be similar to the proteins reportedly involved in solvent stress response in other Gram-positive bacteria, significant role of proline in the proline-glutamate-arginine metabolism was substantiated. Detection of intracellular proline and glutamate accumulation, as well as glutamate transient conversion during butanol exposure confirmed their necessity, especially proline, for cellular butanol tolerance. Disruption of the particular genes in proline biosynthesis pathways clarified the essential role of the anabolic ProB-ProA-ProI system over the osmoadaptive ProH-ProA-ProJ system for cellular protection in response to butanol exposure. Molecular modifications to increase gene dosage for proline biosynthesis as well as for glutamate acquisition enhanced butanol tolerance of B. subtilis 168 up to 1.8% (vol/vol) under the conditions tested. CONCLUSION This work revealed the important role of proline as an effective compatible solute that is required to protect cells against butanol chaotropic effect and to maintain cellular functions in B. subtilis 168 during butanol exposure. Nevertheless, the accumulation of intracellular proline against butanol stress required a metabolic conversion of glutamate through the specific biosynthetic ProB-ProA-ProI route. Thus, exogenous addition of glutamate, but not proline, enhanced butanol tolerance. These findings serve as a practical knowledge to enhance B. subtilis 168 butanol tolerance, and demonstrate means to engineer the bacterial host to promote higher butanol/alcohol tolerance of B. subtilis 168 for the production of butanol and other alcohol biocommodities.
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Affiliation(s)
- Gumpanat Mahipant
- Biological Sciences Program, Faculty of Science, Chulalongkorn University, Bangkok, 10330 Thailand
- Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330 Thailand
| | - Atchara Paemanee
- Proteomics Research Laboratory, Genome Institute Biotechnology, National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathum Thani, 12120 Thailand
| | - Sittiruk Roytrakul
- Proteomics Research Laboratory, Genome Institute Biotechnology, National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathum Thani, 12120 Thailand
| | - Junichi Kato
- Department of Molecular Biotechnology, Graduate School of Advanced Sciences of Matter, Hiroshima University, Hiroshima, 739-8530 Japan
| | - Alisa S. Vangnai
- Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330 Thailand
- Center of Excellence on Hazardous Substance Management (HSM), Chulalongkorn University, Bangkok, 10330 Thailand
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Motwalli O, Essack M, Jankovic BR, Ji B, Liu X, Ansari HR, Hoehndorf R, Gao X, Arold ST, Mineta K, Archer JAC, Gojobori T, Mijakovic I, Bajic VB. In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria. BMC Genomics 2017; 18:33. [PMID: 28056772 PMCID: PMC5217662 DOI: 10.1186/s12864-016-3389-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 12/07/2016] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Finding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable; thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated. RESULTS Here we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis. CONCLUSION To our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.
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Affiliation(s)
- Olaa Motwalli
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Magbubah Essack
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Boris R. Jankovic
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Boyang Ji
- Division of Systems & Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Xinyao Liu
- SABIC Corporate Research and Development (CRD), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Hifzur Rahman Ansari
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering (BESE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Robert Hoehndorf
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Xin Gao
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Stefan T. Arold
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Katsuhiko Mineta
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - John A. C. Archer
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Takashi Gojobori
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
| | - Ivan Mijakovic
- Division of Systems & Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Vladimir B. Bajic
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900 Kingdom of Saudi Arabia
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Paulo JA, O'Connell JD, Everley RA, O'Brien J, Gygi MA, Gygi SP. Quantitative mass spectrometry-based multiplexing compares the abundance of 5000 S. cerevisiae proteins across 10 carbon sources. J Proteomics 2016; 148:85-93. [PMID: 27432472 DOI: 10.1016/j.jprot.2016.07.005] [Citation(s) in RCA: 139] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 06/26/2016] [Accepted: 07/07/2016] [Indexed: 12/18/2022]
Abstract
UNLABELLED The budding yeast Saccharomyces cerevisiae is a model system for investigating biological processes. Cellular events are known to be dysregulated due to shifts in carbon sources. However, the comprehensive proteomic alterations thereof have not been fully investigated. Here we examined proteomic alterations in S. cerevisiae due to the adaptation of yeast from glucose to nine different carbon sources - maltose, trehalose, fructose, sucrose, glycerol, acetate, pyruvate, lactic acid, and oleate. Isobaric tag-based mass spectrometry techniques are at the forefront of global proteomic investigations. As such, we used a TMT10-plex strategy to study multiple growth conditions in a single experiment. The SPS-MS3 method on an Orbitrap Fusion Lumos mass spectrometer enabled the quantification of over 5000 yeast proteins across ten carbon sources at a 1% protein-level FDR. On average, the proteomes of yeast cultured in fructose and sucrose deviated the least from those cultured in glucose. As expected, gene ontology classification revealed the major alteration in protein abundances occurred in metabolic pathways and mitochondrial proteins. Our protocol lays the groundwork for further investigation of carbon source-induced protein alterations. Additionally, these data offer a hypothesis-generating resource for future studies aiming to investigate both characterized and uncharacterized genes. BIOLOGICAL SIGNIFICANCE We investigate the proteomic alterations in S. cerevisiae resulting from adaptation of yeast from glucose to nine different carbon sources - maltose, trehalose, fructose, sucrose, glycerol, acetate, pyruvate, lactic acid, and oleate. SPS-MS3 TMT10plex analysis is used for quantitative proteomic analysis. We showcase a technique that allows the quantification of over 5000 yeast proteins, the highest number to date in S. cerevisiae, across 10 growth conditions in a single experiment. As expected, gene ontology classification of proteins with the major alterations in abundances occurred in metabolic pathways and mitochondrial proteins, reflecting the degree of metabolic stress when cellular machinery shifts from growth on glucose to an alternative carbon source. Our protocol lays the groundwork for further investigation of carbon source-induced protein alterations. Improving depth of coverage - measuring abundance changes of over 5000 proteins - increases our understanding of difficult-to-study genes in the model system S. cerevisiae and by homology human cell biology. We submit this highly comprehensive dataset as a hypothesis generating resource for targeted studies on uncharacterized genes.
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Affiliation(s)
- Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States.
| | - Jeremy D O'Connell
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States
| | - Robert A Everley
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States
| | - Jonathon O'Brien
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States
| | - Micah A Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States.
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Advances in proteomics for production strain analysis. Curr Opin Biotechnol 2015; 35:111-7. [DOI: 10.1016/j.copbio.2015.05.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Revised: 04/28/2015] [Accepted: 05/12/2015] [Indexed: 11/22/2022]
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Paulo JA, O'Connell JD, Gaun A, Gygi SP. Proteome-wide quantitative multiplexed profiling of protein expression: carbon-source dependency in Saccharomyces cerevisiae. Mol Biol Cell 2015; 26:4063-74. [PMID: 26399295 PMCID: PMC4710237 DOI: 10.1091/mbc.e15-07-0499] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Accepted: 09/18/2015] [Indexed: 12/27/2022] Open
Abstract
A mass spectrometry–based tandem mass tag 9-plex strategy was used to determine alterations in relative protein abundance due to three carbon sources—glucose, galactose, and raffinose. More than 4700 proteins were quantified across all nine samples; 1003 demonstrated statistically significant differences in abundance in at least one condition. The global proteomic alterations in the budding yeast Saccharomyces cerevisiae due to differences in carbon sources can be comprehensively examined using mass spectrometry–based multiplexing strategies. In this study, we investigate changes in the S. cerevisiae proteome resulting from cultures grown in minimal media using galactose, glucose, or raffinose as the carbon source. We used a tandem mass tag 9-plex strategy to determine alterations in relative protein abundance due to a particular carbon source, in triplicate, thereby permitting subsequent statistical analyses. We quantified more than 4700 proteins across all nine samples; 1003 proteins demonstrated statistically significant differences in abundance in at least one condition. The majority of altered proteins were classified as functioning in metabolic processes and as having cellular origins of plasma membrane and mitochondria. In contrast, proteins remaining relatively unchanged in abundance included those having nucleic acid–related processes, such as transcription and RNA processing. In addition, the comprehensiveness of the data set enabled the analysis of subsets of functionally related proteins, such as phosphatases, kinases, and transcription factors. As a resource, these data can be mined further in efforts to understand better the roles of carbon source fermentation in yeast metabolic pathways and the alterations observed therein, potentially for industrial applications, such as biofuel feedstock production.
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Affiliation(s)
- Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115
| | | | - Aleksandr Gaun
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115
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