The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Engineering Yeast Transcription Machinery for Improved Ethanol Tolerance and Production
Abstract
Global transcription machinery engineering (gTME) is an approach for reprogramming gene transcription to elicit cellular phenotypes important for technological applications. Here we show the application of gTME to Saccharomyces cerevisiae for improved glucose/ethanol tolerance, a key trait for many biofuels programs. Mutagenesis of the transcription factor Spt15p and selection led to dominant mutations that conferred increased tolerance and more efficient glucose conversion to ethanol. The desired phenotype results from the combined effect of three separate mutations in the SPT15 gene [serine substituted for phenylalanine (Phe 177 Ser) and, similarly, Tyr 195 His, and Lys 218 Arg]. Thus, gTME can provide a route to complex phenotypes that are not readily accessible by traditional methods.
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“For example, laboratory selection can lead to large-scale rewiring of gene regulatory networks, but an approach, that the authors called gTME, global transcription machinery engineering, can also yield similar results [2].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [2]
Citations
Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Co-crystal structure of TBP recognizing the minor groove of a TATA element
Kim, J. L., Nikolov, D. B., & Burley, S. K. (1993) · Nature · doi:10.1038/365520a0 · Cited by 1,065
Huisinga, K. L., & Pugh, B. F. (2004) · Molecular Cell · doi:10.1016/s1097-2765(04)00087-5 · Cited by 561
Molecular Genetics of the RNA Polymerase II General Transcriptional Machinery
Hampsey, M. (1998) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.62.2.465-503.1998 · Cited by 561
Structure and mechanism of the RNA polymerase II transcription machinery
Hahn, S. (2004) · Nature Structural & Molecular Biology · doi:10.1038/nsmb763 · Cited by 546
Redundant roles for the TFIID and SAGA complexes in global transcription
Lee, T. I., Causton, H. C., Holstege, F. C. P., Shen, W.-C., Hannett, N. M., Jennings, E. G., Winston, F., Green, M. R., & Young, R. A. (2000) · Nature · doi:10.1038/35015104 · Cited by 357
Crystal Structure of the Yeast TFIIA/TBP/DNA Complex
Geiger, J. H., Hahn, S., Lee, S., & Sigler, P. B. (1996) · Science · doi:10.1126/science.272.5263.830 · Cited by 263
Nissen, T. L., Kielland‐Brandt, M. C., Nielsen, J., & Villadsen, J. (2000) · Metabolic Engineering · doi:10.1006/mben.1999.0140 · Cited by 232
Schultz, M. C., Reeder, R. H., & Hahn, S. (1992) · Cell · doi:10.1016/0092-8674(92)90233-3 · Cited by 230
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Research works printed but not linked: 2
- H. Alper thesis Massachusetts Institute of Technology (2006).
- D. K. Lee, J. DeJong, S. Hashimoto, M. Horikoshi, R. G. Roeder, Mol. Cell. Biol.12, 5189 (1992).
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“1 转录因子全局扰动 针对细胞非特定生化途径所关联的复杂性 状,比如高产和胁迫抗性,其改造提升往往需要 对细胞内在的代谢进行彻底的重编程,这就需要 同时改变很多基因的表达水平,难以通过连续的 多基因修饰来实现。全局转录机器工程 (gTME) 是通过改造和进化全局转录因子、转录机器等关 键蛋白,构建高度多样、复杂的转录调控突变文 库,在转录水平上产生新型的丰富多样性,实现对 基因表达网络和细胞代谢重编程,并以定向进化方 式加以迭代,从而使细胞获得所期望的表型([46])。 gTME 是一种从转录全局角度工程改造复杂性状 的普适性方法。自 2006 年开发以来([47]),该方法 已成功地应用于原核生物和真核生物系统,比如 酿酒酵母、…”
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Glebes, T. Y. (2014) · CU Scholar (University of Colorado Boulder)
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(2007) · Yeast · doi:10.1002/yea.1328
(2012) · Wiley eBooks · doi:10.1002/9781118414514.refs
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(2008) · CRC Press eBooks · doi:10.1201/9781420051254.ch3
Clay, S. M., & Fong, S. S. (2012) · SpringerBriefs in systems biology · doi:10.1007/978-1-4614-5580-6_4
(2007) · Asia-Pacific Biotech News · doi:10.1142/s0219030307000614
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Cowan, D. A., Tuffin, I. M., & Robb, F. T. (2009) · Springer eBooks · doi:10.1007/978-3-540-77587-4_259
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Jacobus, A. P., Cavassana, S. D., de Oliveira, I. I., Barreto, J. A., Rohwedder, E., Frazzon, J., Basso, T. P., Basso, L. C., & Gross, J. (2024) · Figshare · doi:10.6084/m9.figshare.26719017
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Additional file 1 of Ethanol tolerance in engineered strains of Clostridium thermocellum
Olson, D. G., Maloney, M., Lanahan, A. A., Cervenka, N. D., Xia, Y., Pech‐Canul, Á., Hon, S., Tian, L., Ziegler, S. J., Bomble, Y. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26617537
Li, Q., Zhao, P., Yin, H., Liu, Z., Zhao, H., & PingFang, T. (2020) · Figshare · doi:10.6084/m9.figshare.12916744
Li, Q., Zhao, P., Yin, H., Liu, Z., Zhao, H., & PingFang, T. (2020) · Figshare · doi:10.6084/m9.figshare.12916732
Mo, Q., & Yuan, J. (2024) · Figshare · doi:10.6084/m9.figshare.24954497
Wang, L., Wang, X., He, Z.-Q., Zhou, S.-J., Xu, L. H., Tan, X.-Y., Xu, T., Li, B.-Z., & Yuan, Y.-J. (2020) · Figshare · doi:10.6084/m9.figshare.13310998
Metadata
- Authors
- Alper, H., Moxley, J., Nevoigt, E., Fink, G. R., & Stephanopoulos, G.
- Affiliations
- Whitehead Institute for Biomedical Research (US)
- Corresponding author
- Stephanopoulos, Gregory
- Venue
- Science
- Published
- 2006-12-08
- Volume
- 314
- Issue
- 5805
- Pages
- 1565-1568
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2080537888
- Cited by
- 823
- References
- 26
- Citations by year
- 2026: 10 · 2025: 23 · 2024: 31 · 2023: 18 · 2022: 28 · 2021: 39 · 2020: 43 · 2019: 37 · 2018: 39 · 2017: 44 · 2016: 49 · 2015: 61 · 2014: 55 · 2013: 57 · 2012: 68
- FWCI
- 14.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of General Medical Sciences (GM035010)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Physical Sciences › Engineering › Biomedical Engineering › Biofuel production and bioconversion
- Keywords
- Saccharomyces cerevisiae, ethanol tolerance, glucose fermentation, transcription factor mutations, dominant mutations, biofuel production, yeast strain engineering
- MeSH terms
- Ethanol, Fermentation, Genetic Engineering, Glucose, Phenotype, Saccharomyces cerevisiae, Transcription Factors, Transcription, Genetic, Transformation, Genetic, Up-Regulation, Gene Expression Regulation, Fungal, Mutagenesis, Cell Cycle Proteins, Amino Acid Substitution, Gene Expression Profiling, Saccharomyces cerevisiae Proteins, TATA-Box Binding Protein, Transcription Factor TFIID, TATA-Binding Protein Associated Factors
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