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Yardımcı BK. Naringenin and caffeic acid increase ethanol production in yeast cells by reducing very high gravity fermentation-related oxidative stress. Braz J Microbiol 2024:10.1007/s42770-024-01525-5. [PMID: 39320639 DOI: 10.1007/s42770-024-01525-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Accepted: 09/17/2024] [Indexed: 09/26/2024] Open
Abstract
Very high gravity (VHG) fermentation is an industrial-scale process utilizing a sugar concentration above 250 g/L to attain a significant ethanol concentration, with the advantages of decreased labor, production costs, water usage, bacterial contamination, and energy consumption. Saccharomyces cerevisiae is one of the most extensively employed organisms in ethanol fermentation through VHG technology. Conversely, high glucose exposure leads to numerous stress factors that negatively impact the ethanol production efficiency of this organism. Here, the impact of various phytochemicals added to the VHG medium on viability, glucose consumption, ethanol production efficiency, total antioxidant-oxidant status (TAS and TOS), and the response of the enzymatic antioxidant system of yeast were investigated. 2.0 mM naringenin and caffeic acid increased ethanol production by 2.453 ± 0.198 and 1.261 ± 0.138-fold, respectively. The glucose consumption rate exhibited a direct relationship with ethanol production in the naringenin-supplemented group. The highest TAS was determined as 0.734 ± 0.044 mmol Trolox Eq./L in the same group. Furthermore, both phytochemical compounds exhibited robust positive correlations with TAS (rnaringenin = 0.9986; rcaffeic acid = 0.9553) and TOS levels (rnaringenin = -0.9824; rcaffeic acid = -0.9791). While naringenin caused statistically significant increases in glutathione reductase (GR) and thioredoxin reductase (TrxR) activities, caffeic acid significantly increased TrxR and superoxide dismutase (SOD). Both phytochemicals seem to impact the ethanol production ability by regulating the redox status of the cells. We believe that the incorporation of particularly cost-effective antioxidants into the fermentation medium may serve as an alternative way to enhance the efficiency of bioethanol production using VHG technology.
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Affiliation(s)
- Berna Kavakcıoğlu Yardımcı
- Department of Chemistry, Faculty of Science, Pamukkale University, Denizli, Turkey.
- Advanced Technology Application and Research Center, Pamukkale University, Denizli, Turkey.
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Turner W, Greetham D, Du C. The characterisation of Wickerhamomyces anomalus M15, a highly tolerant yeast for bioethanol production using seaweed derived medium. Front Bioeng Biotechnol 2022; 10:1028185. [PMID: 36312543 PMCID: PMC9608644 DOI: 10.3389/fbioe.2022.1028185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Advanced generation biofuels have potential for replacing fossil fuels as society moves forward into a net-zero carbon future. Marine biomass is a promising source of fermentable sugars for fermentative bioethanol production; however the medium derived from seaweed hydrolysis contains various inhibitors, such as salts that affected ethanol fermentation efficiency. In this study the stress tolerance of a marine yeast, Wickerhamomyces anomalus M15 was characterised. Specific growth rate analysis results showed that Wickerhamomyces anomalus M15 could tolerate up to 600 g/L glucose, 150 g/L xylose and 250 g/L ethanol, respectively. Using simulated concentrated seaweed hydrolysates, W. anomalus M15’s bioethanol production potential using macroalgae derived feedstocks was assessed, in which 5.8, 45.0, and 19.9 g/L ethanol was produced from brown (Laminaria digitata), green (Ulva linza) and red seaweed (Porphyra umbilicalis) based media. The fermentation of actual Ulva spp. hydrolysate harvested from United Kingdom shores resulted in a relatively low ethanol concentration (15.5 g/L) due to challenges that arose from concentrating the seaweed hydrolysate. However, fed-batch fermentation using simulated concentrated green seaweed hydrolysate achieved a concentration of 73 g/L ethanol in fermentations using both seawater and reverse osmosis water. Further fermentations conducted with an adaptive strain W. anomalus M15-500A showed improved bioethanol production of 92.7 g/L ethanol from 200 g/L glucose and reduced lag time from 93 h to 24 h in fermentation with an initial glucose concentration of 500 g/L. The results indicated that strains W. anomalus M15 and W. anomalus M15-500A have great potential for industrial bioethanol production using marine biomass derived feedstocks. It also suggested that if a concentrated high sugar content seaweed hydrolysate could be obtained, the bioethanol concentration could achieve 90 g/L or above, exceeding the minimum industrial production threshold.
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Affiliation(s)
- William Turner
- School of Applied Science, University of Huddersfield, Huddersfield, United Kingdom
| | - Darren Greetham
- School of Applied Science, University of Huddersfield, Huddersfield, United Kingdom
- Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, United Kingdom
| | - Chenyu Du
- School of Applied Science, University of Huddersfield, Huddersfield, United Kingdom
- *Correspondence: Chenyu Du,
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Wu L, Lyu Y, Wu P, Luo T, Zeng J, Shi T, Zhou J, Yu Y, Lu H. Meiosis-Based Laboratory Evolution of the Thermal Tolerance in Kluyveromyces marxianus. Front Bioeng Biotechnol 2022; 9:799756. [PMID: 35087802 PMCID: PMC8786734 DOI: 10.3389/fbioe.2021.799756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 12/20/2021] [Indexed: 12/04/2022] Open
Abstract
Kluyveromyces marxianus is the fastest-growing eukaryote and a promising host for producing bioethanol and heterologous proteins. To perform a laboratory evolution of thermal tolerance in K. marxianus, diploid, triploid and tetraploid strains were constructed, respectively. Considering the genetic diversity caused by genetic recombination in meiosis, we established an iterative cycle of “diploid/polyploid - meiosis - selection of spores at high temperature” to screen thermotolerant strains. Results showed that the evolution of thermal tolerance in diploid strain was more efficient than that in triploid and tetraploid strains. The thermal tolerance of the progenies of diploid and triploid strains after a two-round screen was significantly improved than that after a one-round screen, while the thermal tolerance of the progenies after the one-round screen was better than that of the initial strain. After a two-round screen, the maximum tolerable temperature of Dip2-8, a progeny of diploid strain, was 3°C higher than that of the original strain. Whole-genome sequencing revealed nonsense mutations of PSR1 and PDE2 in the thermotolerant progenies. Deletion of either PSR1 or PDE2 in the original strain improved thermotolerance and two deletions displayed additive effects, suggesting PSR1 and PDE2 negatively regulated the thermotolerance of K. marxianus in parallel pathways. Therefore, the iterative cycle of “meiosis - spore screening” developed in this study provides an efficient way to perform the laboratory evolution of heat resistance in yeast.
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Affiliation(s)
- Li Wu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Yilin Lyu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Pingping Wu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Tongyu Luo
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Junyuan Zeng
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Tianfang Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Jungang Zhou
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
| | - Yao Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
- *Correspondence: Yao Yu, ; Hong Lu,
| | - Hong Lu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, China
- Shanghai Collaborative Innovation Center for Biomanufacturing Technology, Shanghai, China
- *Correspondence: Yao Yu, ; Hong Lu,
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Hospet R, Thangadurai D, Cruz-Martins N, Sangeetha J, Anu Appaiah KA, Chowdhury ZZ, Bedi N, Soytong K, Al Tawahaj ARM, Jabeen S, Tallur MM. Genome shuffling for phenotypic improvement of industrial strains through recursive protoplast fusion technology. Crit Rev Food Sci Nutr 2021:1-10. [PMID: 34592865 DOI: 10.1080/10408398.2021.1983763] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Strains' improvement technology plays an essential role in enhancing the quality of industrial strains. Several traditional methods and modern techniques have been used to further improve strain engineering programs. The advances stated in strain engineering and the increasing demand for microbial metabolites leads to the invention of the genome shuffling technique, which ensures a specific phenotype improvement through inducing mutation and recursive protoplast fusion. In such technique, the selection of multi-parental strains with distinct phenotypic traits is crucial. In addition, as this evolutionary strain improvement technique involves combinative approaches, it does not require any gene sequence data for genome alteration and, therefore, strains developed by this elite technique will not be considered as genetically modified organisms. In this review, the different stages involved in the genome shuffling technique and its wide applications in various phenotype improvements will be addressed. Taken together, data discussed here highlight that the use of genome shuffling for strain improvement will be a plus for solving complex phenotypic traits and in promoting the rapid development of other industrially important strains.
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Affiliation(s)
| | | | - Natália Cruz-Martins
- Faculty of Medicine, University of Porto, Porto, Portugal.,Institute for Research and Innovation in Health (i3S), University of Porto, Porto, Portugal.,Institute of Research and Advanced Training in Health Sciences and Technologies (CESPU), Gandra PRD, Portugal
| | - Jeyabalan Sangeetha
- Department of Environmental Science, Central University of Kerala, Kasaragod, Kerala, India
| | - Konerira Aiyappa Anu Appaiah
- Department of Microbiology and Fermentation Technology, Central Food Technological Research Institute (CSIR), Mysore, Karnataka, India
| | - Zaira Zaman Chowdhury
- Nanotechnology and Catalysis Research Center (NANOCAT), Institute of Advanced Studies (IAS), University of Malaya, Kuala Lumpur, Malaysia
| | - Namita Bedi
- Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India
| | - Kasem Soytong
- Department of Plant Production Technology, King Mongkut's Institute of Technology Ladkrabang (KMITL), Ladkrabang, Bangkok, Thailand
| | | | - Shoukat Jabeen
- Department of Botany, Karnatak University, Dharwad, Karnataka, India
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Adebami GE, Kuila A, Ajunwa OM, Fasiku SA, Asemoloye MD. Genetics and metabolic engineering of yeast strains for efficient ethanol production. J FOOD PROCESS ENG 2021. [DOI: 10.1111/jfpe.13798] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
| | - Arindam Kuila
- Department of Bioscience and Biotechnology Banasthali University Vanasthali India
| | - Obinna M. Ajunwa
- Department of Microbiology Modibbo Adama University of Technology Yola Nigeria
| | - Samuel A. Fasiku
- Department of Biological Sciences Ajayi Crowther University Oyo Nigeria
| | - Michael D. Asemoloye
- Department of Pharmaceutical Science and Technology Tianjin University Tianjin China
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6
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Wang L, Li B, Wang SP, Xia ZY, Gou M, Tang YQ. Improving multiple stress-tolerance of a flocculating industrial Saccharomyces cerevisiae strain by random mutagenesis and hybridization. Process Biochem 2021. [DOI: 10.1016/j.procbio.2020.12.022] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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7
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Ruchala J, Kurylenko OO, Dmytruk KV, Sibirny AA. Construction of advanced producers of first- and second-generation ethanol in Saccharomyces cerevisiae and selected species of non-conventional yeasts (Scheffersomyces stipitis, Ogataea polymorpha). J Ind Microbiol Biotechnol 2019; 47:109-132. [PMID: 31637550 PMCID: PMC6970964 DOI: 10.1007/s10295-019-02242-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 10/01/2019] [Indexed: 12/20/2022]
Abstract
This review summarizes progress in the construction of efficient yeast ethanol producers from glucose/sucrose and lignocellulose. Saccharomyces cerevisiae is the major industrial producer of first-generation ethanol. The different approaches to increase ethanol yield and productivity from glucose in S. cerevisiae are described. Construction of the producers of second-generation ethanol is described for S. cerevisiae, one of the best natural xylose fermenters, Scheffersomyces stipitis and the most thermotolerant yeast known Ogataea polymorpha. Each of these organisms has some advantages and drawbacks. S. cerevisiae is the primary industrial ethanol producer and is the most ethanol tolerant natural yeast known and, however, cannot metabolize xylose. S. stipitis can effectively ferment both glucose and xylose and, however, has low ethanol tolerance and requires oxygen for growth. O. polymorpha grows and ferments at high temperatures and, however, produces very low amounts of ethanol from xylose. Review describes how the mentioned drawbacks could be overcome.
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Affiliation(s)
- Justyna Ruchala
- Department of Microbiology and Biotechnology, University of Rzeszow, Zelwerowicza 4, 35-601, Rzeszow, Poland
| | - Olena O Kurylenko
- Department of Molecular Genetics and Biotechnology, Institute of Cell Biology, NAS of Ukraine, Drahomanov Street, 14/16, Lviv, 79005, Ukraine
| | - Kostyantyn V Dmytruk
- Department of Molecular Genetics and Biotechnology, Institute of Cell Biology, NAS of Ukraine, Drahomanov Street, 14/16, Lviv, 79005, Ukraine
| | - Andriy A Sibirny
- Department of Microbiology and Biotechnology, University of Rzeszow, Zelwerowicza 4, 35-601, Rzeszow, Poland.
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8
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Mo W, Wang M, Zhan R, Yu Y, He Y, Lu H. Kluyveromyces marxianus developing ethanol tolerance during adaptive evolution with significant improvements of multiple pathways. BIOTECHNOLOGY FOR BIOFUELS 2019; 12:63. [PMID: 30949239 PMCID: PMC6429784 DOI: 10.1186/s13068-019-1393-z] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 03/06/2019] [Indexed: 05/12/2023]
Abstract
BACKGROUND Kluyveromyces marxianus, the known fastest-growing eukaryote on the earth, has remarkable thermotolerance and capacity to utilize various agricultural residues to produce low-cost bioethanol, and hence is industrially important to resolve the imminent energy shortage crisis. Currently, the poor ethanol tolerance hinders its operable application in the industry, and it is necessary to improve K. marxianus' ethanol resistance and unravel the underlying systematical mechanisms. However, this has been seldom reported to date. RESULTS We carried out a wild-type haploid K. marxianus FIM1 in adaptive evolution in 6% (v/v) ethanol. After 100-day evolution, the KM-100d population was obtained; its ethanol tolerance increased up to 10% (v/v). Interestingly, DNA analysis and RNA-seq analysis showed that KM-100d yeasts' ethanol tolerance improvement was not due to ploidy change or meaningful mutations, but founded on transcriptional reprogramming in a genome-wide range. Even growth in an ethanol-free medium, many genes in KM-100d maintained their up-regulation. Especially, pathways of ethanol consumption, membrane lipid biosynthesis, anti-osmotic pressure, anti-oxidative stress, and protein folding were generally up-regulated in KM-100d to resist ethanol. Notably, enhancement of the secretory pathway may be the new strategy KM-100d developed to anti-osmotic pressure, instead of the traditional glycerol production way in S. cerevisiae. Inferred from the transcriptome data, besides ethanol tolerance, KM-100d may also develop the ability to resist osmotic, oxidative, and thermic stresses, and this was further confirmed by the cell viability test. Furthermore, under such environmental stresses, KM-100d greatly improved ethanol production than the original strain. In addition, we found that K. marxianus may adopt distinct routes to resist different ethanol concentrations. Trehalose biosynthesis was required for low ethanol, while sterol biosynthesis and the whole secretory pathway were activated for high ethanol. CONCLUSIONS This study reveals that ethanol-driven laboratory evolution could improve K. marxianus' ethanol tolerance via significant up-regulation of multiple pathways including anti-osmotic, anti-oxidative, and anti-thermic processes, and indeed consequently raised ethanol yield in industrial high-temperature and high-ethanol circumstance. Our findings give genetic clues for further rational optimization of K. marxianus' ethanol production, and also partly confirm the positively correlated relationship between yeast's ethanol tolerance and production.
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Affiliation(s)
- Wenjuan Mo
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, 200438 China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, 200438 China
| | - Mengzhu Wang
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, 200438 China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, 200438 China
| | - Rongrong Zhan
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, 200438 China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, 200438 China
| | - Yao Yu
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, 200438 China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, 200438 China
| | - Yungang He
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032 China
| | - Hong Lu
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, 200438 China
- Shanghai Engineering Research Center of Industrial Microorganisms, Shanghai, 200438 China
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Tian K, Li Y, Wang B, Wu H, Caiyin Q, Zhang Z, Qiao J. The genome and transcriptome of Lactococcus lactis ssp. lactis F44 and G423: Insights into adaptation to the acidic environment. J Dairy Sci 2018; 102:1044-1058. [PMID: 30594364 DOI: 10.3168/jds.2018-14882] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 10/27/2018] [Indexed: 12/13/2022]
Abstract
Nisin, as a common green (environmentally friendly), nontoxic antibacterial peptide secreted by Lactococcus lactis, is widely used to prevent the decomposition of meat and dairy products and maintains relatively high stability at low pH. However, the growth of Lc. lactis is frequently inhibited by high lactic acid concentrations produced during fermentation. This phenomenon has become a great challenge in enhancing the nisin yield for this strain. Here, the shuffled strain G423 that could survive on a solid plate at pH 3.7 was generated through protoplast fusion-mediated genome shuffling. The nisin titer of G423 peaked at 4,543 IU/mL, which was 59.9% higher than that of the same batch of the initial strain Lc. lactis F44. The whole genome comparisons between G423 and F44 indicated that 6 large fragments (86,725 bp) were inserted in G423 compared with that of Lc. lactis F44. Transcriptome data revealed that 4 novel noncoding transcripts, and the significantly upregulated genes were involved in multiple processes in G423. In particular, the expression of genes involved in cell wall and membrane biosynthesis was obviously perturbed under acidic stress. Quantitative real-time PCR analysis showed that the transcription of noncoding small RNA NC-1 increased by 2.35-fold at pH 3.0 compared with that of the control (pH 7.0). Overexpression assays indicated that small RNA NC-1 could significantly enhance the acid tolerance and nisin production of G423 and F44. Our work provided new insights into the sophisticated genetic mechanisms involved in Lc. lactis in an acidic environment, which might elucidate its potential application in food and dairy industries.
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Affiliation(s)
- Kairen Tian
- Department of Pharmaceutical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjian 300072, P.R. China
| | - Yanni Li
- Department of Pharmaceutical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjian 300072, P.R. China
| | - Binbin Wang
- Department of Pharmaceutical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjian 300072, P.R. China
| | - Hao Wu
- Department of Pharmaceutical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjian 300072, P.R. China
| | - Qinggele Caiyin
- Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjian 300072, P.R. China
| | - Zhijun Zhang
- Forestry and Fruit Research Institute of Tianjin Academy of Agricultural Sciences, Tianjin 300072, P.R. China
| | - Jianjun Qiao
- Department of Pharmaceutical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjian 300072, P.R. China; SynBio Research Platform Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, P.R. China.
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10
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Kim B, Kim HS. Identification of novel genes to assign enhanced tolerance to osmotic stress in Saccharomyces cerevisiae. FEMS Microbiol Lett 2018; 365:5040221. [PMID: 29931330 DOI: 10.1093/femsle/fny149] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 06/18/2018] [Indexed: 11/14/2022] Open
Abstract
Saccharomyces cerevisiae strains tolerant to osmotic stress are important for ethanol production during very high gravity (VHG) fermentation. We aimed to identify novel genes that confer enhanced tolerance to osmotic stress in S. cerevisiae. Two strains tolerant to up to 30% (w/v) glucose were isolated by screening a transposon-mediated mutant library. Two genes were identified: TIS11 and SDS23. In addition, the ability of these genes to confer osmotic stress tolerance was demonstrated by disrupting and overexpressing the open reading frame of each gene. The two transposon mutants grew faster than the control strain in YPD rich medium containing 30% (w/v) glucose and showed activation of Hog1p in response to VHG glucose. The disruption of genes identified in this study, TIS11 and SDS23, provides a basis for improved tolerance to osmotic stress under VHG fermentation condition.
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Affiliation(s)
- Bora Kim
- Division of Biomedicinal Chemistry and Cosmetics, Mokwon University, 88, Doanbuk-ro, Seo-gu, Daejeon, 35349, Republic of Korea
| | - Hyun-Soo Kim
- Department of Food Science and Technology, Jungwon University, 85, Munmu-ro, Goesan-eup, Goesan-gun, Chungbuk 28024, Republic of Korea
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11
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Evolutionary engineering of industrial microorganisms-strategies and applications. Appl Microbiol Biotechnol 2018; 102:4615-4627. [DOI: 10.1007/s00253-018-8937-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Revised: 03/13/2018] [Accepted: 03/13/2018] [Indexed: 10/17/2022]
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12
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Kordowska-Wiater M, Lisiecka U, Kostro K. Improvement of Candida parapsilosis by genome shuffling for the efficient production of arabitol from l-arabinose. Food Sci Biotechnol 2018; 27:1395-1403. [PMID: 30319849 PMCID: PMC6170280 DOI: 10.1007/s10068-018-0369-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Revised: 03/16/2018] [Accepted: 03/27/2018] [Indexed: 01/07/2023] Open
Abstract
Arabitol is used in the food industry as a low-calorie sweetener. It is produced by yeasts during the biotransformation process of l-arabinose. Genome shuffling was performed in Candida parapsilosis DSM 70125, an efficient producer of arabitol, to obtain fusants with improved arabitol production ability. Four mutants from the parental library were used for the first round of genome shuffling. The best fusants, GSI-1 and GSI-10A, were subjected to a second round of genome shuffling. Finally, two fusants, GSII-3 and GSII-16, produced concentrations of arabitol that were 50% higher than that of the wild-type strain during selection culture. Under the optimal conditions established for C. parapsilosis, the two fusants produced 11.83 and 11.75 g/L of arabitol and were approximately 15-16% more efficient than the wild-type strain. Flow cytometry analysis showed that the ploidy of the new strains did not change.
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Affiliation(s)
- Monika Kordowska-Wiater
- 1Department of Biotechnology, Microbiology and Human Nutrition, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland
| | - Urszula Lisiecka
- 2Department of Epizootiology and Clinic of Infectious Diseases, University of Life Sciences in Lublin, Głęboka 30, 20-950 Lublin, Poland
| | - Krzysztof Kostro
- 2Department of Epizootiology and Clinic of Infectious Diseases, University of Life Sciences in Lublin, Głęboka 30, 20-950 Lublin, Poland
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Yin H, Liu M, Deng Y, Zhao J, Yu J, Dong J, Yang M. Reduced acetaldehyde production by genome shuffling of an industrial brewing yeast strain. JOURNAL OF THE INSTITUTE OF BREWING 2017. [DOI: 10.1002/jib.457] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Hua Yin
- State Key Laboratory of Biological Fermentation Engineering of Beer; Tsingtao Brewery Co. Ltd; Qingdao 266061 People's Republic of China
| | - Ming Liu
- China National Research Institute of Food and Fermentation Industries; Beijing 100015 People's Republic of China
| | - Yang Deng
- State Key Laboratory of Biological Fermentation Engineering of Beer; Tsingtao Brewery Co. Ltd; Qingdao 266061 People's Republic of China
| | - Junfeng Zhao
- College of Food Science and Engineering; Henan University of Science and Technology; Luoyang 471003 People's Republic of China
| | - Junhong Yu
- State Key Laboratory of Biological Fermentation Engineering of Beer; Tsingtao Brewery Co. Ltd; Qingdao 266061 People's Republic of China
| | - Jianjun Dong
- State Key Laboratory of Biological Fermentation Engineering of Beer; Tsingtao Brewery Co. Ltd; Qingdao 266061 People's Republic of China
| | - Mei Yang
- State Key Laboratory of Biological Fermentation Engineering of Beer; Tsingtao Brewery Co. Ltd; Qingdao 266061 People's Republic of China
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Wickramasinghe GHIM, Rathnayake PPAMSI, Chandrasekharan NV, Weerasinghe MSS, Wijesundera RLC, Wijesundera WSS. Expression, Docking, and Molecular Dynamics of Endo- β-1,4-xylanase I Gene of Trichoderma virens in Pichia stipitis. BIOMED RESEARCH INTERNATIONAL 2017; 2017:4658584. [PMID: 28856159 PMCID: PMC5569632 DOI: 10.1155/2017/4658584] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 06/19/2017] [Indexed: 11/18/2022]
Abstract
It is essential that major carbohydrate polymers in the lignocellulosic biomass are converted into fermentable sugars for the economical production of energy. Xylan, the major component of hemicelluloses, is the second most naturally abundant carbohydrate polymer comprising 20-40% of the total biomass. Endoxylanase (EXN) hydrolyzes xylan into mixtures of xylooligosaccharides. The objective of this study was to genetically modify Pichia stipitis, a pentose sugar fermenting yeast species, to hydrolyze xylan into xylooligosaccharides via cloning and heterologous extracellular expression of EXNI gene from locally isolated Trichoderma virens species. Pichia stipitis was engineered to carry the EXNI gene of T. virens using pGAPZα expression vector. The open reading frame encodes 191 amino acids and SDS-PAGE analysis revealed a 24 kDA recombinant protein. The EXNI activity expressed by recombinant P. stipitis clone under standard conditions using 1% beechwood xylan was 31.7 U/ml. Molecular docking and molecular dynamics simulations were performed to investigate EXNI-xylan interactions. Free EXNI and xylan bound EXNI exhibited similar stabilities and structural behavior in aqueous medium. Furthermore, this in silico work opens avenues for the development of newer generation EXN proteins that can perform better and have enhanced catalytic activity.
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15
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Deparis Q, Claes A, Foulquié-Moreno MR, Thevelein JM. Engineering tolerance to industrially relevant stress factors in yeast cell factories. FEMS Yeast Res 2017; 17:3861662. [PMID: 28586408 PMCID: PMC5812522 DOI: 10.1093/femsyr/fox036] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 06/04/2017] [Indexed: 01/01/2023] Open
Abstract
The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way.
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Affiliation(s)
- Quinten Deparis
- Laboratory of Molecular Cell Biology, Institute of Botany and Microbiology, B-3001 KU Leuven, Belgium
- Center for Microbiology, VIB, Kasteelpark Arenberg 31, B-3001 Leuven-Heverlee, Flanders, Belgium
| | - Arne Claes
- Laboratory of Molecular Cell Biology, Institute of Botany and Microbiology, B-3001 KU Leuven, Belgium
- Center for Microbiology, VIB, Kasteelpark Arenberg 31, B-3001 Leuven-Heverlee, Flanders, Belgium
| | - Maria R. Foulquié-Moreno
- Laboratory of Molecular Cell Biology, Institute of Botany and Microbiology, B-3001 KU Leuven, Belgium
- Center for Microbiology, VIB, Kasteelpark Arenberg 31, B-3001 Leuven-Heverlee, Flanders, Belgium
| | - Johan M. Thevelein
- Laboratory of Molecular Cell Biology, Institute of Botany and Microbiology, B-3001 KU Leuven, Belgium
- Center for Microbiology, VIB, Kasteelpark Arenberg 31, B-3001 Leuven-Heverlee, Flanders, Belgium
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16
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Xie ZX, Li BZ, Mitchell LA, Wu Y, Qi X, Jin Z, Jia B, Wang X, Zeng BX, Liu HM, Wu XL, Feng Q, Zhang WZ, Liu W, Ding MZ, Li X, Zhao GR, Qiao JJ, Cheng JS, Zhao M, Kuang Z, Wang X, Martin JA, Stracquadanio G, Yang K, Bai X, Zhao J, Hu ML, Lin QH, Zhang WQ, Shen MH, Chen S, Su W, Wang EX, Guo R, Zhai F, Guo XJ, Du HX, Zhu JQ, Song TQ, Dai JJ, Li FF, Jiang GZ, Han SL, Liu SY, Yu ZC, Yang XN, Chen K, Hu C, Li DS, Jia N, Liu Y, Wang LT, Wang S, Wei XT, Fu MQ, Qu LM, Xin SY, Liu T, Tian KR, Li XN, Zhang JH, Song LX, Liu JG, Lv JF, Xu H, Tao R, Wang Y, Zhang TT, Deng YX, Wang YR, Li T, Ye GX, Xu XR, Xia ZB, Zhang W, Yang SL, Liu YL, Ding WQ, Liu ZN, Zhu JQ, Liu NZ, Walker R, Luo Y, Wang Y, Shen Y, Yang H, Cai Y, Ma PS, Zhang CT, Bader JS, Boeke JD, Yuan YJ. "Perfect" designer chromosome V and behavior of a ring derivative. Science 2017; 355:eaaf4704. [PMID: 28280151 DOI: 10.1126/science.aaf4704] [Citation(s) in RCA: 154] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 01/30/2017] [Indexed: 03/28/2024]
Abstract
Perfect matching of an assembled physical sequence to a specified designed sequence is crucial to verify design principles in genome synthesis. We designed and de novo synthesized 536,024-base pair chromosome synV in the "Build-A-Genome China" course. We corrected an initial isolate of synV to perfectly match the designed sequence using integrative cotransformation and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated editing in 22 steps; synV strains exhibit high fitness under a variety of culture conditions, compared with that of wild-type V strains. A ring synV derivative was constructed, which is fully functional in Saccharomyces cerevisiae under all conditions tested and exhibits lower spore viability during meiosis. Ring synV chromosome can extends Sc2.0 design principles and provides a model with which to study genomic rearrangement, ring chromosome evolution, and human ring chromosome disorders.
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Affiliation(s)
- Ze-Xiong Xie
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Bing-Zhi Li
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Leslie A Mitchell
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, Langone Medical Center, New York University, New York City, NY 10016, USA
| | - Yi Wu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xin Qi
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Zhu Jin
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Bin Jia
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xia Wang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Bo-Xuan Zeng
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Hui-Min Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xiao-Le Wu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Qi Feng
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Wen-Zheng Zhang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Wei Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ming-Zhu Ding
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xia Li
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Guang-Rong Zhao
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jian-Jun Qiao
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jing-Sheng Cheng
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Meng Zhao
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Zheng Kuang
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, Langone Medical Center, New York University, New York City, NY 10016, USA
| | - Xuya Wang
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, Langone Medical Center, New York University, New York City, NY 10016, USA
| | - J Andrew Martin
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, Langone Medical Center, New York University, New York City, NY 10016, USA
| | - Giovanni Stracquadanio
- High Throughput Biology Center and Department of Biomedical Engineering, Johns Hopkins University, Baltimore 21205, MD, USA
- School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, England, UK
| | - Kun Yang
- High Throughput Biology Center and Department of Biomedical Engineering, Johns Hopkins University, Baltimore 21205, MD, USA
| | - Xue Bai
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Juan Zhao
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Meng-Long Hu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Qiu-Hui Lin
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Wen-Qian Zhang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ming-Hua Shen
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Si Chen
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Wan Su
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - En-Xu Wang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Rui Guo
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Fang Zhai
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xue-Jiao Guo
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Hao-Xing Du
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jia-Qing Zhu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Tian-Qing Song
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jun-Jun Dai
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Fei-Fei Li
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Guo-Zhen Jiang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Shi-Lei Han
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Shi-Yang Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Zhi-Chao Yu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xiao-Na Yang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ken Chen
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Cheng Hu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Da-Shuai Li
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Nan Jia
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Yue Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Lin-Ting Wang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Su Wang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xiao-Tong Wei
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Mei-Qing Fu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Lan-Meng Qu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Si-Yu Xin
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ting Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Kai-Ren Tian
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xue-Nan Li
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jin-Hua Zhang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Li-Xiang Song
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jin-Gui Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jia-Fei Lv
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Hang Xu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ran Tao
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Yan Wang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ting-Ting Zhang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ye-Xuan Deng
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Yi-Ran Wang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ting Li
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Guang-Xin Ye
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Xiao-Ran Xu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Zheng-Bao Xia
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Wei Zhang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Shi-Lan Yang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Yi-Lin Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Wen-Qi Ding
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Zhen-Ning Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Jun-Qi Zhu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Ning-Zhi Liu
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
| | - Roy Walker
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, Scotland, UK
| | - Yisha Luo
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, Scotland, UK
| | - Yun Wang
- BGI-Shenzhen, Shenzhen 518083, PR China
| | - Yue Shen
- BGI-Shenzhen, Shenzhen 518083, PR China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen 518083, PR China
- James D. Watson Institute of Genome Sciences, Hangzhou 310058, PR China
| | - Yizhi Cai
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, Scotland, UK
| | - Ping-Sheng Ma
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
| | - Chun-Ting Zhang
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China
| | - Joel S Bader
- High Throughput Biology Center and Department of Biomedical Engineering, Johns Hopkins University, Baltimore 21205, MD, USA
| | - Jef D Boeke
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, Langone Medical Center, New York University, New York City, NY 10016, USA
| | - Ying-Jin Yuan
- Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China.
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, PR China
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17
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Affiliation(s)
- Tao Jin
- Iowa State University; Department of Chemical and Biological Engineering; 2114 Sweeney Hall, 618 Bissell Rd. Ames, IA 50011 USA
| | - Jieni Lian
- Iowa State University; Department of Chemical and Biological Engineering; 2114 Sweeney Hall, 618 Bissell Rd. Ames, IA 50011 USA
| | - Laura R. Jarboe
- Iowa State University; Department of Chemical and Biological Engineering; 2114 Sweeney Hall, 618 Bissell Rd. Ames, IA 50011 USA
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Luna‐Flores CH, Palfreyman RW, Krömer JO, Nielsen LK, Marcellin E. Improved production of propionic acid using genome shuffling. Biotechnol J 2016; 12. [DOI: 10.1002/biot.201600120] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Revised: 09/22/2016] [Accepted: 09/23/2016] [Indexed: 11/05/2022]
Affiliation(s)
- Carlos H Luna‐Flores
- Australian Institute for Bioengineering and Nanotechnology (AIBN) The University of Queensland Brisbane Qld Australia
| | - Robin W Palfreyman
- Australian Institute for Bioengineering and Nanotechnology (AIBN) The University of Queensland Brisbane Qld Australia
| | - Jens O Krömer
- Australian Institute for Bioengineering and Nanotechnology (AIBN) The University of Queensland Brisbane Qld Australia
| | - Lars K Nielsen
- Australian Institute for Bioengineering and Nanotechnology (AIBN) The University of Queensland Brisbane Qld Australia
| | - Esteban Marcellin
- Australian Institute for Bioengineering and Nanotechnology (AIBN) The University of Queensland Brisbane Qld Australia
- Dow Centre for Sustainable Engineering and Innovation The University of Queensland Brisbane Qld Australia
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19
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Building cellular pathways and programs enabled by the genetic diversity of allo-genomes and meta-genomes. Curr Opin Biotechnol 2015; 36:16-31. [DOI: 10.1016/j.copbio.2015.08.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 08/06/2015] [Accepted: 08/09/2015] [Indexed: 12/21/2022]
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20
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Caspeta L, Castillo T, Nielsen J. Modifying Yeast Tolerance to Inhibitory Conditions of Ethanol Production Processes. Front Bioeng Biotechnol 2015; 3:184. [PMID: 26618154 PMCID: PMC4641163 DOI: 10.3389/fbioe.2015.00184] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2015] [Accepted: 10/28/2015] [Indexed: 11/17/2022] Open
Abstract
Saccharomyces cerevisiae strains having a broad range of substrate utilization, rapid substrate consumption, and conversion to ethanol, as well as good tolerance to inhibitory conditions are ideal for cost-competitive ethanol production from lignocellulose. A major drawback to directly design S. cerevisiae tolerance to inhibitory conditions of lignocellulosic ethanol production processes is the lack of knowledge about basic aspects of its cellular signaling network in response to stress. Here, we highlight the inhibitory conditions found in ethanol production processes, the targeted cellular functions, the key contributions of integrated -omics analysis to reveal cellular stress responses according to these inhibitors, and current status on design-based engineering of tolerant and efficient S. cerevisiae strains for ethanol production from lignocellulose.
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Affiliation(s)
- Luis Caspeta
- Centro de Investigación en Biotecnología, Universidad Autónoma del Estado de Morelos , Cuernavaca , Mexico
| | - Tania Castillo
- Centro de Investigación en Biotecnología, Universidad Autónoma del Estado de Morelos , Cuernavaca , Mexico
| | - Jens Nielsen
- Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology , Gothenburg , Sweden ; Department of Biology and Biological Engineering, Chalmers University of Technology , Gothenburg , Sweden ; Novo Nordisk Foundation Center for Biosustainability , Hørsholm , Denmark
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21
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Petruzzi L, Rosaria Corbo M, Sinigaglia M, Bevilacqua A. Brewer’s yeast in controlled and uncontrolled fermentations, with a focus on novel, nonconventional, and superior strains. FOOD REVIEWS INTERNATIONAL 2015. [DOI: 10.1080/87559129.2015.1075211] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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22
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Park WK, Yang JW, Kim HS. Identification of novel genes responsible for salt tolerance by transposon mutagenesis in Saccharomyces cerevisiae. ACTA ACUST UNITED AC 2015; 42:567-75. [DOI: 10.1007/s10295-015-1584-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Accepted: 01/09/2015] [Indexed: 10/24/2022]
Abstract
Abstract
Saccharomyces cerevisiae strains tolerant to salt stress are important for the production of single-cell protein using kimchi waste brine. In this study, two strains (TN-1 and TN-2) tolerant of up to 10 % (w/v) NaCl were isolated by screening a transposon-mediated mutant library. The determination of transposon insertion sites and Northern blot analysis identified two genes, MDJ1 and VPS74, and revealed disruptions of the open reading frame of both genes, indicating that salt tolerance can be conferred. Such tolerant phenotypes reverted to sensitive phenotypes on the autologous or overexpression of each gene. The two transposon mutants grew faster than the control strain when cultured at 30 °C in rich medium containing 5, 7.5 or 10 % NaCl. The genes identified in this study may provide a basis for application in developing industrial yeast strains.
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Affiliation(s)
- Won-Kun Park
- grid.37172.30 0000000122920500 Department of Chemical and Biomolecular Engineering KAIST 291, Daehak-ro, Yuseong-gu 350-701 Daejeon Korea
| | - Ji-Won Yang
- grid.37172.30 0000000122920500 Department of Chemical and Biomolecular Engineering KAIST 291, Daehak-ro, Yuseong-gu 350-701 Daejeon Korea
| | - Hyun-Soo Kim
- grid.440940.d 0000000404463336 Department of Food Science and Industry Jungwon University 85, Munmu-ro, Goesan-eup, Goesan-gun 367-805 Chungbuk Korea
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23
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Hou LH, Meng M, Guo L, He JY. A comparison of whole cell directed evolution approaches in breeding of industrial strain of Saccharomyces cerevisiae. Biotechnol Lett 2015; 37:1393-8. [PMID: 25773199 DOI: 10.1007/s10529-015-1812-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2015] [Accepted: 03/02/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE To reduce the fermentation cost in very high gravity fermentations of ethanol using Saccharomyces cerevisiae, whole cell directed evolution approaches were carried out. RESULTS The methods used included cell ploidy manipulation, global transcription machinery engineering and genome shuffling. Ethanol production by the four methods was improved compared with the control. Notably, the ethanol yield of a strain constructed by genome shuffling was enhanced by up to 11 % more than the control reaching 120 g ethanol/l in 35 h using a very high gravity fermentation with 300 g glucose/l. CONCLUSION Genome shuffling can create strains with improved fermentation characteristics in very high gravity fermentations.
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Affiliation(s)
- Li-Hua Hou
- Key Laboratory of Food Nutrition and Safety, Tianjin University of Science & Technology, Ministry of Education, Tianjin, 300457, China,
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24
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Snoek T, Picca Nicolino M, Van den Bremt S, Mertens S, Saels V, Verplaetse A, Steensels J, Verstrepen KJ. Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance. BIOTECHNOLOGY FOR BIOFUELS 2015; 8:32. [PMID: 25759747 PMCID: PMC4354739 DOI: 10.1186/s13068-015-0216-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2014] [Accepted: 01/29/2015] [Indexed: 05/26/2023]
Abstract
BACKGROUND During the final phases of bioethanol fermentation, yeast cells face high ethanol concentrations. This stress results in slower or arrested fermentations and limits ethanol production. Novel Saccharomyces cerevisiae strains with superior ethanol tolerance may therefore allow increased yield and efficiency. Genome shuffling has emerged as a powerful approach to rapidly enhance complex traits including ethanol tolerance, yet previous efforts have mostly relied on a mutagenized pool of a single strain, which can potentially limit the effectiveness. Here, we explore novel robot-assisted strategies that allow to shuffle the genomes of multiple parental yeasts on an unprecedented scale. RESULTS Screening of 318 different yeasts for ethanol accumulation, sporulation efficiency, and genetic relatedness yielded eight heterothallic strains that served as parents for genome shuffling. In a first approach, the parental strains were subjected to multiple consecutive rounds of random genome shuffling with different selection methods, yielding several hybrids that showed increased ethanol tolerance. Interestingly, on average, hybrids from the first generation (F1) showed higher ethanol production than hybrids from the third generation (F3). In a second approach, we applied several successive rounds of robot-assisted targeted genome shuffling, yielding more than 3,000 targeted crosses. Hybrids selected for ethanol tolerance showed increased ethanol tolerance and production as compared to unselected hybrids, and F1 hybrids were on average superior to F3 hybrids. In total, 135 individual F1 and F3 hybrids were tested in small-scale very high gravity fermentations. Eight hybrids demonstrated superior fermentation performance over the commercial biofuel strain Ethanol Red, showing a 2 to 7% increase in maximal ethanol accumulation. In an 8-l pilot-scale test, the best-performing hybrid fermented medium containing 32% (w/v) glucose to dryness, yielding 18.7% (v/v) ethanol with a productivity of 0.90 g ethanol/l/h and a yield of 0.45 g ethanol/g glucose. CONCLUSIONS We report the use of several different large-scale genome shuffling strategies to obtain novel hybrids with increased ethanol tolerance and fermentation capacity. Several of the novel hybrids show best-parent heterosis and outperform the commonly used bioethanol strain Ethanol Red, making them interesting candidate strains for industrial production.
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Affiliation(s)
- Tim Snoek
- />Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU Leuven, Kasteelpark Arenberg 22, 3001 Leuven, Belgium
- />Laboratory for Systems Biology, VIB, Bio-Incubator, Gaston Geenslaan 1, 3001 Leuven, Belgium
| | - Martina Picca Nicolino
- />Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU Leuven, Kasteelpark Arenberg 22, 3001 Leuven, Belgium
- />Laboratory for Systems Biology, VIB, Bio-Incubator, Gaston Geenslaan 1, 3001 Leuven, Belgium
| | - Stefanie Van den Bremt
- />Laboratory of Enzyme, Fermentation and Brewing Technology, KU Leuven technologiecampus Ghent, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium
| | - Stijn Mertens
- />Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU Leuven, Kasteelpark Arenberg 22, 3001 Leuven, Belgium
- />Laboratory for Systems Biology, VIB, Bio-Incubator, Gaston Geenslaan 1, 3001 Leuven, Belgium
| | - Veerle Saels
- />Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU Leuven, Kasteelpark Arenberg 22, 3001 Leuven, Belgium
- />Laboratory for Systems Biology, VIB, Bio-Incubator, Gaston Geenslaan 1, 3001 Leuven, Belgium
| | - Alex Verplaetse
- />Laboratory of Enzyme, Fermentation and Brewing Technology, KU Leuven technologiecampus Ghent, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium
| | - Jan Steensels
- />Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU Leuven, Kasteelpark Arenberg 22, 3001 Leuven, Belgium
- />Laboratory for Systems Biology, VIB, Bio-Incubator, Gaston Geenslaan 1, 3001 Leuven, Belgium
| | - Kevin J Verstrepen
- />Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU Leuven, Kasteelpark Arenberg 22, 3001 Leuven, Belgium
- />Laboratory for Systems Biology, VIB, Bio-Incubator, Gaston Geenslaan 1, 3001 Leuven, Belgium
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25
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Genetic improvement of native xylose-fermenting yeasts for ethanol production. J Ind Microbiol Biotechnol 2014; 42:1-20. [DOI: 10.1007/s10295-014-1535-z] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Accepted: 11/02/2014] [Indexed: 12/27/2022]
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26
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Inoue H, Hashimoto S, Matsushika A, Watanabe S, Sawayama S. Breeding of a xylose-fermenting hybrid strain by mating genetically engineered haploid strains derived from industrial Saccharomyces cerevisiae. J Ind Microbiol Biotechnol 2014; 41:1773-81. [PMID: 25355632 DOI: 10.1007/s10295-014-1531-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2014] [Accepted: 10/18/2014] [Indexed: 01/04/2023]
Abstract
The industrial Saccharomyces cerevisiae IR-2 is a promising host strain to genetically engineer xylose-utilizing yeasts for ethanol fermentation from lignocellulosic hydrolysates. Two IR-2-based haploid strains were selected based upon the rate of xylulose fermentation, and hybrids were obtained by mating recombinant haploid strains harboring heterogeneous xylose dehydrogenase (XDH) (wild-type NAD(+)-dependent XDH or engineered NADP(+)-dependent XDH, ARSdR), xylose reductase (XR) and xylulose kinase (XK) genes. ARSdR in the hybrids selected for growth rates on yeast extract-peptone-dextrose (YPD) agar and YP-xylose agar plates typically had a higher activity than NAD(+)-dependent XDH. Furthermore, the xylose-fermenting performance of the hybrid strain SE12 with the same level of heterogeneous XDH activity was similar to that of a recombinant strain of IR-2 harboring a single set of genes, XR/ARSdR/XK. These results suggest not only that the recombinant haploid strains retain the appropriate genetic background of IR-2 for ethanol production from xylose but also that ARSdR is preferable for xylose fermentation.
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Affiliation(s)
- Hiroyuki Inoue
- Biomass Refinery Research Center (BRRC), National Institute of Advanced Industrial Science and Technology (AIST), 3-11-32 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-0046, Japan,
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27
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Steensels J, Snoek T, Meersman E, Nicolino MP, Voordeckers K, Verstrepen KJ. Improving industrial yeast strains: exploiting natural and artificial diversity. FEMS Microbiol Rev 2014; 38:947-95. [PMID: 24724938 PMCID: PMC4293462 DOI: 10.1111/1574-6976.12073] [Citation(s) in RCA: 257] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2013] [Revised: 01/31/2014] [Accepted: 04/02/2014] [Indexed: 12/23/2022] Open
Abstract
Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as 'global transcription machinery engineering' (gTME), to induce genetic variation, providing a new source of yeast genetic diversity.
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Affiliation(s)
- Jan Steensels
- Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU LeuvenLeuven, Belgium
- Laboratory for Systems Biology, VIBLeuven, Belgium
| | - Tim Snoek
- Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU LeuvenLeuven, Belgium
- Laboratory for Systems Biology, VIBLeuven, Belgium
| | - Esther Meersman
- Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU LeuvenLeuven, Belgium
- Laboratory for Systems Biology, VIBLeuven, Belgium
| | - Martina Picca Nicolino
- Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU LeuvenLeuven, Belgium
- Laboratory for Systems Biology, VIBLeuven, Belgium
| | - Karin Voordeckers
- Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU LeuvenLeuven, Belgium
- Laboratory for Systems Biology, VIBLeuven, Belgium
| | - Kevin J Verstrepen
- Laboratory for Genetics and Genomics, Centre of Microbial and Plant Genetics (CMPG), KU LeuvenLeuven, Belgium
- Laboratory for Systems Biology, VIBLeuven, Belgium
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Direct ethanol production from lignocellulosic sugars and sugarcane bagasse by a recombinant Trichoderma reesei strain HJ48. ScientificWorldJournal 2014; 2014:798683. [PMID: 24995362 PMCID: PMC4060538 DOI: 10.1155/2014/798683] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2014] [Accepted: 05/10/2014] [Indexed: 11/18/2022] Open
Abstract
Trichoderma reesei can be considered as a candidate for consolidated bioprocessing (CBP) microorganism. However, its ethanol yield needs to be improved significantly. Here the ethanol production of T. reesei CICC 40360 was improved by genome shuffling while simultaneously enhancing the ethanol resistance. The initial mutant population was generated by nitrosoguanidine treatment of the spores, and an improved population producing more than fivefold ethanol than wild type was obtained by genome shuffling. The results show that the shuffled strain HJ48 can efficiently convert lignocellulosic sugars to ethanol under aerobic conditions. Furthermore, it was able to produce ethanol directly from sugarcane bagasse, demonstrating that the shuffled strain HJ48 is a suitable microorganism for consolidated bioprocessing.
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29
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Wang H, Ji B, Ren H, Meng C. The relationship between lysine 4 on histone H3 methylation levels of alcohol tolerance genes and changes of ethanol tolerance in Saccharomyces cerevisiae. Microb Biotechnol 2014; 7:307-14. [PMID: 24779776 PMCID: PMC4241724 DOI: 10.1111/1751-7915.12121] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2013] [Revised: 12/31/2013] [Accepted: 01/22/2013] [Indexed: 01/09/2023] Open
Abstract
We evaluated whether epigenetic changes contributed to improve ethanol tolerance in mutant
populations of Saccharomyces cerevisiae (S. cerevisiae). Two
ethanol-tolerant variants of S. cerevisiae were used to evaluate the genetic
stability in the process of stress-free passage cultures. We found that acquired ethanol tolerance
was lost and transcription level of some genes (HSP104, PRO1,
TPS1, and SOD1) closely related to ethanol tolerance decreased
significantly after the 10th passage in ethanol-free medium. Tri-methylation of lysine 4 on histone
H3 (H3K4) enhanced at the promoter of HSP104, PRO1,
TPS1 and SOD1 in ethanol-tolerant variants of S.
cerevisiae was also diminished after tenth passage in stress-free cultures. The ethanol
tolerance was reacquired when exogenous SOD1 transferred in some tolerance-lost
strains. This showed that H3K4 methylation is involved in phenotypic variation with regard to
ethanol tolerance with respect to classic breeding methods used in yeast.
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Affiliation(s)
- Hang Wang
- Department of Bioengineering, College of Biological Science and Biotechnology, Fuzhou University, Fuzhou, Fujian, China
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Evolutionary engineering by genome shuffling. Appl Microbiol Biotechnol 2014; 98:3877-87. [PMID: 24595425 DOI: 10.1007/s00253-014-5616-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Revised: 02/11/2014] [Accepted: 02/12/2014] [Indexed: 01/28/2023]
Abstract
An upsurge in the bioeconomy drives the need for engineering microorganisms with increasingly complex phenotypes. Gains in productivity of industrial microbes depend on the development of improved strains. Classical strain improvement programmes for the generation, screening and isolation of such mutant strains have existed for several decades. An alternative to traditional strain improvement methods, genome shuffling, allows the directed evolution of whole organisms via recursive recombination at the genome level. This review deals chiefly with the technical aspects of genome shuffling. It first presents the diversity of organisms and phenotypes typically evolved using this technology and then reviews available sources of genetic diversity and recombination methodologies. Analysis of the literature reveals that genome shuffling has so far been restricted to microorganisms, both prokaryotes and eukaryotes, with an overepresentation of antibiotics- and biofuel-producing microbes. Mutagenesis is the main source of genetic diversity, with few studies adopting alternative strategies. Recombination is usually done by protoplast fusion or sexual recombination, again with few exceptions. For both diversity and recombination, prospective methods that have not yet been used are also presented. Finally, the potential of genome shuffling for gaining insight into the genetic basis of complex phenotypes is also discussed.
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31
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Shi J, Zhang M, Zhang L, Wang P, Jiang L, Deng H. Xylose-fermenting Pichia stipitis by genome shuffling for improved ethanol production. Microb Biotechnol 2014; 7:90-9. [PMID: 24393385 PMCID: PMC3937714 DOI: 10.1111/1751-7915.12092] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2013] [Revised: 09/04/2013] [Accepted: 09/09/2013] [Indexed: 11/27/2022] Open
Abstract
Xylose fermentation is necessary for the bioconversion of lignocellulose to ethanol as fuel, but wild-type Saccharomyces cerevisiae strains cannot fully metabolize xylose. Several efforts have been made to obtain microbial strains with enhanced xylose fermentation. However, xylose fermentation remains a serious challenge because of the complexity of lignocellulosic biomass hydrolysates. Genome shuffling has been widely used for the rapid improvement of industrially important microbial strains. After two rounds of genome shuffling, a genetically stable, high-ethanol-producing strain was obtained. Designated as TJ2-3, this strain could ferment xylose and produce 1.5 times more ethanol than wild-type Pichia stipitis after fermentation for 96 h. The acridine orange and propidium iodide uptake assays showed that the maintenance of yeast cell membrane integrity is important for ethanol fermentation. This study highlights the importance of genome shuffling in P. stipitis as an effective method for enhancing the productivity of industrial strains.
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Affiliation(s)
- Jun Shi
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai, China
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32
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Stewart GG, Hill AE, Russell I. 125thAnniversary Review: Developments in brewing and distilling yeast strains. JOURNAL OF THE INSTITUTE OF BREWING 2013. [DOI: 10.1002/jib.104] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Graham G. Stewart
- 13 Heol Nant Castan, Rhiwbina Cardiff CF14 6RP UK
- ICBD; Heriot-Watt University; Riccarton Edinburgh EH14 4AS UK
| | - Annie E. Hill
- ICBD; Heriot-Watt University; Riccarton Edinburgh EH14 4AS UK
| | - Inge Russell
- ICBD; Heriot-Watt University; Riccarton Edinburgh EH14 4AS UK
- Alltech Inc.; Nicholasville KY 40356 USA
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Mutations of the TATA-binding protein confer enhanced tolerance to hyperosmotic stress in Saccharomyces cerevisiae. Appl Microbiol Biotechnol 2013; 97:8227-38. [PMID: 23709042 DOI: 10.1007/s00253-013-4985-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2013] [Revised: 04/28/2013] [Accepted: 05/05/2013] [Indexed: 11/27/2022]
Abstract
Previously, it was shown that overexpression of either of two SPT15 mutant alleles, SPT15-M2 and SPT15-M3, which encode mutant TATA-binding proteins, confer enhanced ethanol tolerance in Saccharomyces cerevisiae. In this study, we demonstrated that strains overexpressing SPT15-M2 or SPT15-M3 were tolerant to hyperosmotic stress caused by high concentrations of glucose, salt, and sorbitol. The enhanced tolerance to high glucose concentrations in particular improved ethanol production from very high gravity (VHG) ethanol fermentations. The strains displayed constitutive and sustained activation of Hog1, a central kinase in the high osmolarity glycerol (HOG) signal transduction pathway of S. cerevisiae. However, the cell growth defect known to be caused by constitutive and sustained activation of Hog1 was not observed. We also found that reactive oxygen species (ROS) were accumulated to a less extent upon exposure to high glucose concentration in our osmotolerant strains. We identified six new genes (GPH1, HSP12, AIM17, SSA4, USV1, and IGD1), the individual deletion of which renders cells sensitive to 50 % glucose. In spite of the presence of multiple copies of stress response element in their promoters, it was apparent that those genes were not controlled at the transcriptional level by the HOG pathway under the high glucose conditions. Combined with previously published results, overexpression of SPT15-M2 or SPT15-M3 clearly provides a basis for improved tolerance to ethanol and osmotic stress, which enables construction of strains of any genetic background that need enhanced tolerance to high concentrations of ethanol and glucose, promoting the feasibility for VHG ethanol fermentation.
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34
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Hou L, Wang M, Wang C, Wang C, Wang H. Analysis of Salt-Tolerance Genes in Zygosaccharomyces rouxii. Appl Biochem Biotechnol 2013; 170:1417-25. [DOI: 10.1007/s12010-013-0283-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2011] [Accepted: 05/03/2013] [Indexed: 11/28/2022]
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35
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Adaptive Evolution of Saccharomyces cerevisiae in a Continuous and Closed Circulating Fermentation (CCCF) System Coupled with PDMS Membrane Pervaporation. Appl Biochem Biotechnol 2013; 169:2362-73. [DOI: 10.1007/s12010-013-0142-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2011] [Accepted: 02/18/2013] [Indexed: 10/27/2022]
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Chen B, Ling H, Chang MW. Transporter engineering for improved tolerance against alkane biofuels in Saccharomyces cerevisiae. BIOTECHNOLOGY FOR BIOFUELS 2013; 6:21. [PMID: 23402697 PMCID: PMC3598725 DOI: 10.1186/1754-6834-6-21] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2012] [Accepted: 02/08/2013] [Indexed: 05/15/2023]
Abstract
BACKGROUND Hydrocarbon alkanes, components of major fossil fuels, are considered as next-generation biofuels because their biological production has recently been shown to be possible. However, high-yield alkane production requires robust host cells that are tolerant against alkanes, which exhibit cytotoxicity. In this study, we aimed to improve alkane tolerance in Saccharomyces cerevisiae, a key industrial microbial host, by harnessing heterologous transporters that potentially pump out alkanes. RESULTS To this end, we attempted to exploit ABC transporters in Yarrowia lipolytica based on the observation that it utilizes alkanes as a carbon source. We confirmed the increased transcription of ABC2 and ABC3 transporters upon exposure to a range of alkanes in Y. lipolytica. We then showed that the heterologous expression of ABC2 and ABC3 transporters significantly increased tolerance against decane and undecane in S. cerevisiae through maintaining lower intracellular alkane level. In particular, ABC2 transporter increased the tolerance limit of S. cerevisiae about 80-fold against decane. Furthermore, through site-directed mutagenesis for glutamate (E988 for ABC2, and E989 for ABC3) and histidine (H1020 for ABC2, and H1021 for ABC3), we provided the evidence that glutamate was essential for the activity of ABC2 and ABC3 transporters, with ATP most likely to be hydrolyzed by a catalytic carboxylate mechanism. CONCLUSIONS Here, we demonstrated that transporter engineering through expression of heterologous efflux pumps led to significantly improved tolerance against alkane biofuels in S. cerevisiae. We believe that our results laid the groundwork for developing robust alkane-producing yeast cells through transporter engineering, which will greatly aid in next-generation alkane biofuel production and recovery.
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Affiliation(s)
- Binbin Chen
- Division of Chemical and Biomolecular Engineering, School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Nanyang 637459, Singapore
| | - Hua Ling
- Division of Chemical and Biomolecular Engineering, School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Nanyang 637459, Singapore
| | - Matthew Wook Chang
- Division of Chemical and Biomolecular Engineering, School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Nanyang 637459, Singapore
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Lo TM, Teo WS, Ling H, Chen B, Kang A, Chang MW. Microbial engineering strategies to improve cell viability for biochemical production. Biotechnol Adv 2013; 31:903-14. [PMID: 23403071 DOI: 10.1016/j.biotechadv.2013.02.001] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2012] [Revised: 02/05/2013] [Accepted: 02/05/2013] [Indexed: 11/16/2022]
Abstract
Efficient production of biochemicals using engineered microbes as whole-cell biocatalysts requires robust cell viability. Robust viability leads to high productivity and improved bioprocesses by allowing repeated cell recycling. However, cell viability is negatively affected by a plethora of stresses, namely chemical toxicity and metabolic imbalances, primarily resulting from bio-synthesis pathways. Chemical toxicity is caused by substrates, intermediates, products, and/or by-products, and these compounds often interfere with important metabolic processes and damage cellular infrastructures such as cell membrane, leading to poor cell viability. Further, stresses on engineered cells are accentuated by metabolic imbalances, which are generated by heavy metabolic resource consumption due to enzyme overexpression, redistribution of metabolic fluxes, and impaired intracellular redox state by co-factor imbalance. To address these challenges, herein, we discuss a range of key microbial engineering strategies, substantiated by recent advances, to improve cell viability for commercially sustainable production of biochemicals from renewable resources.
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Affiliation(s)
- Tat-Ming Lo
- School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459, Singapore
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Kim SR, Lee KS, Kong II, Lesmana A, Lee WH, Seo JH, Kweon DH, Jin YS. Construction of an efficient xylose-fermenting diploid Saccharomyces cerevisiae strain through mating of two engineered haploid strains capable of xylose assimilation. J Biotechnol 2013; 164:105-11. [PMID: 23376240 DOI: 10.1016/j.jbiotec.2012.12.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2012] [Revised: 12/07/2012] [Accepted: 12/27/2012] [Indexed: 12/17/2022]
Abstract
Saccharomyces cerevisiae can be engineered for xylose fermentation through introduction of wild type or mutant genes (XYL1/XYL1 (R276H), XYL2, and XYL3) coding for xylose metabolic enzymes from Scheffersomyces stipitis. The resulting engineered strains, however, often yielded undesirable phenotypes such as slow xylose assimilation and xylitol accumulation. In this study, we performed the mating of two engineered strains that exhibit suboptimal xylose-fermenting phenotypes in order to develop an improved xylose-fermenting diploid strain. Specifically, we obtained two engineered haploid strains (YSX3 and SX3). The YSX3 strain consumed xylose rapidly and produced a lot of xylitol. On the contrary, the SX3 strain consumed xylose slowly with little xylitol production. After converting the mating type of SX3 from alpha to a, the resulting strain (SX3-2) was mated with YSX3 to construct a heterozygous diploid strain (KSM). The KSM strain assimilated xylose (0.25gxyloseh(-1)gcells(-1)) as fast as YSX3 and accumulated a small amount of xylitol (0.03ggxylose(-1)) as low as SX3, resulting in an improved ethanol yield (0.27ggxylose(-1)). We found that the improvement in xylose fermentation by the KSM strain was not because of heterozygosity or genome duplication but because of the complementation of the two xylose-metabolic pathways. This result suggested that mating of suboptimal haploid strains is a promising strategy to develop engineered yeast strains with improved xylose fermenting capability.
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Affiliation(s)
- Soo Rin Kim
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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Zhang W, Geng A. Improved ethanol production by a xylose-fermenting recombinant yeast strain constructed through a modified genome shuffling method. BIOTECHNOLOGY FOR BIOFUELS 2012; 5:46. [PMID: 22809265 PMCID: PMC3463424 DOI: 10.1186/1754-6834-5-46] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2011] [Accepted: 01/11/2012] [Indexed: 05/18/2023]
Abstract
BACKGROUND Xylose is the second most abundant carbohydrate in the lignocellulosic biomass hydrolysate. The fermentation of xylose is essential for the bioconversion of lignocelluloses to fuels and chemicals. However the wild-type strains of Saccharomyces cerevisiae are unable to utilize xylose. Many efforts have been made to construct recombinant yeast strains to enhance xylose fermentation over the past few decades. Xylose fermentation remains challenging due to the complexity of lignocellulosic biomass hydrolysate. In this study, a modified genome shuffling method was developed to improve xylose fermentation by S. cerevisiae. Recombinant yeast strains were constructed by recursive DNA shuffling with the recombination of entire genome of P. stipitis with that of S. cerevisiae. RESULTS After two rounds of genome shuffling and screening, one potential recombinant yeast strain ScF2 was obtained. It was able to utilize high concentration of xylose (100 g/L to 250 g/L xylose) and produced ethanol. The recombinant yeast ScF2 produced ethanol more rapidly than the naturally occurring xylose-fermenting yeast, P. stipitis, with improved ethanol titre and much more enhanced xylose tolerance. CONCLUSION The modified genome shuffling method developed in this study was more effective and easier to operate than the traditional protoplast-fusion-based method. Recombinant yeast strain ScF2 obtained in this study was a promising candidate for industrial cellulosic ethanol production. In order to further enhance its xylose fermentation performance, ScF2 needs to be additionally improved by metabolic engineering and directed evolution.
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Affiliation(s)
- Wei Zhang
- School of Life Sciences and Chemical Technology, Ngee Ann Polytechnic, 535 Clementi Road, Singapore, 599489, Singapore
| | - Anli Geng
- School of Life Sciences and Chemical Technology, Ngee Ann Polytechnic, 535 Clementi Road, Singapore, 599489, Singapore
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A genome shuffling-generated Saccharomyces cerevisiae isolate that ferments xylose and glucose to produce high levels of ethanol. ACTA ACUST UNITED AC 2012; 39:777-87. [DOI: 10.1007/s10295-011-1076-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2010] [Accepted: 12/15/2011] [Indexed: 11/26/2022]
Abstract
Abstract
Genome shuffling is an efficient approach for the rapid improvement of industrially important microbial phenotypes. This report describes optimized conditions for protoplast preparation, regeneration, inactivation, and fusion using the Saccharomyces cerevisiae W5 strain. Ethanol production was confirmed by TTC (triphenyl tetrazolium chloride) screening and high-performance liquid chromatography (HPLC). A genetically stable, high ethanol-producing strain that fermented xylose and glucose was obtained following three rounds of genome shuffling. After fermentation for 84 h, the high ethanol-producing S. cerevisiae GS3-10 strain (which utilized 69.48 and 100% of the xylose and glucose stores, respectively) produced 26.65 g/L ethanol, i.e., 47.08% higher than ethanol production by S. cerevisiae W5 (18.12 g/L). The utilization ratios of xylose and glucose were 69.48 and 100%, compared to 14.83 and 100% for W5, respectively. The ethanol yield was 0.40 g/g (ethanol/consumed glucose and xylose), i.e., 17.65% higher than the yield by S. cerevisiae W5 (0.34 g/g).
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Wang PM, Zheng DQ, Liu TZ, Tao XL, Feng MG, Min H, Jiang XH, Wu XC. The combination of glycerol metabolic engineering and drug resistance marker-aided genome shuffling to improve very-high-gravity fermentation performances of industrial Saccharomyces cerevisiae. BIORESOURCE TECHNOLOGY 2012; 108:203-210. [PMID: 22269055 DOI: 10.1016/j.biortech.2011.12.147] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Revised: 12/29/2011] [Accepted: 12/30/2011] [Indexed: 05/31/2023]
Abstract
A challenge associated with the ethanol productivity under very-high-gravity (VHG) conditions, optimizing multi-traits (i.e. byproduct formation and stress tolerance) of industrial yeast strains, is overcome by a combination of metabolic engineering and genome shuffling. First, industrial strain Y12 was deleted with a glycerol exporter Fps1p and hetero-expressed with glyceraldehydes-3-phosphate dehydrogenase, resulting in the modified strain YFG12 with lower glycerol yield. Second, YFG12 was subjected to three rounds of drug resistance marker-aided genome shuffling to increase its ethanol tolerance, and the best shuffled strain TS5 was obtained. Compared with wild strain Y12, shuffled strain TS5 not only decreased glycerol formation by 14.8%, but also increased fermentation rate and ethanol yield by 3.7% and 7.6%, respectively. Moreover, the system of genetic modification and Cre/loxP in aid of three different drug-resistance markers presented in the study significantly improved breeding efficiency and will facilitate the application of breeding technologies in prototrophic industrial microorganisms.
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Affiliation(s)
- Pin-Mei Wang
- College of Life Sciences, Zhejiang University, Hangzhou, 310058 Zhejiang, PR China
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A novel strategy to construct yeast Saccharomyces cerevisiae strains for very high gravity fermentation. PLoS One 2012; 7:e31235. [PMID: 22363590 PMCID: PMC3281935 DOI: 10.1371/journal.pone.0031235] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2011] [Accepted: 01/04/2012] [Indexed: 12/01/2022] Open
Abstract
Very high gravity (VHG) fermentation is aimed to considerably increase both the fermentation rate and the ethanol concentration, thereby reducing capital costs and the risk of bacterial contamination. This process results in critical issues, such as adverse stress factors (ie., osmotic pressure and ethanol inhibition) and high concentrations of metabolic byproducts which are difficult to overcome by a single breeding method. In the present paper, a novel strategy that combines metabolic engineering and genome shuffling to circumvent these limitations and improve the bioethanol production performance of Saccharomyces cerevisiae strains under VHG conditions was developed. First, in strain Z5, which performed better than other widely used industrial strains, the gene GPD2 encoding glycerol 3-phosphate dehydrogenase was deleted, resulting in a mutant (Z5ΔGPD2) with a lower glycerol yield and poor ethanol productivity. Second, strain Z5ΔGPD2 was subjected to three rounds of genome shuffling to improve its VHG fermentation performance, and the best performing strain SZ3-1 was obtained. Results showed that strain SZ3-1 not only produced less glycerol, but also increased the ethanol yield by up to 8% compared with the parent strain Z5. Further analysis suggested that the improved ethanol yield in strain SZ3-1 was mainly contributed by the enhanced ethanol tolerance of the strain. The differences in ethanol tolerance between strains Z5 and SZ3-1 were closely associated with the cell membrane fatty acid compositions and intracellular trehalose concentrations. Finally, genome rearrangements in the optimized strain were confirmed by karyotype analysis. Hence, a combination of genome shuffling and metabolic engineering is an efficient approach for the rapid improvement of yeast strains for desirable industrial phenotypes.
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Challenges of the utilization of wood polymers: how can they be overcome? Appl Microbiol Biotechnol 2011; 91:1525-36. [DOI: 10.1007/s00253-011-3350-z] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2011] [Revised: 04/30/2011] [Accepted: 05/01/2011] [Indexed: 01/05/2023]
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Liu JJ, Ding WT, Zhang GC, Wang JY. Improving ethanol fermentation performance of Saccharomyces cerevisiae in very high-gravity fermentation through chemical mutagenesis and meiotic recombination. Appl Microbiol Biotechnol 2011; 91:1239-46. [DOI: 10.1007/s00253-011-3404-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2011] [Revised: 05/02/2011] [Accepted: 05/22/2011] [Indexed: 11/29/2022]
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Improvement of robustness and ethanol production of ethanologenic Saccharomyces cerevisiae under co-stress of heat and inhibitors. J Ind Microbiol Biotechnol 2011; 39:73-80. [PMID: 21698486 DOI: 10.1007/s10295-011-1001-0] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2011] [Accepted: 06/07/2011] [Indexed: 10/18/2022]
Abstract
Bioethanol is an attractive alternative to fossil fuels. Saccharomyces cerevisiae is the most important ethanol producer. However, yeast cells are challenged by various environmental stresses during the industrial process of ethanol production. The robustness under heat, acetic acid, and furfural stresses was improved for ethanologenic S. cerevisiae in this work using genome shuffling. Recombinant yeast strain R32 could grow at 45°C, and resist 0.55% (v/v) acetic acid and 0.3% (v/v) furfural at 40°C. When ethanol fermentation was conducted at temperatures ranging from 30 to 42°C, recombinant strain R32 always gave high ethanol production. After 42 h of fermentation at 42°C, 187.6 ± 1.4 g/l glucose was utilized by recombinant strain R32 to produce 81.4 ± 2.7 g/l ethanol, which were respectively 3.4 and 4.1 times those of CE25. After 36 h of fermentation at 40°C with 0.5% (v/v) acetic acid, 194.4 ± 1.2 g/l glucose in the medium was utilized by recombinant strain R32 to produce 84.2 ± 4.6 g/l of ethanol. The extent of glucose utilization and ethanol concentration of recombinant strain R32 were 6.3 and 7.9 times those of strain CE25. The ethanol concentration produced by recombinant strain R32 was 8.9 times that of strain CE25 after fermentation for 48 h under 0.2% (v/v) furfural stress at 40°C. The strong physiological robustness and fitness of yeast strain R32 support its potential application for industrial production of bioethanol from renewable resources such as lignocelluloses.
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46
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Saccharomyces cerevisiae genome shuffling through recursive population mating leads to improved tolerance to spent sulfite liquor. Appl Environ Microbiol 2011; 77:4736-43. [PMID: 21622800 DOI: 10.1128/aem.02769-10] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Spent sulfite liquor (SSL) is a waste effluent from sulfite pulping that contains monomeric sugars which can be fermented to ethanol. However, fermentative yeasts used for the fermentation of the sugars in SSL are adversely affected by the inhibitory substances in this complex feedstock. To overcome this limitation, evolutionary engineering of Saccharomyces cerevisiae was carried out using genome-shuffling technology based on large-scale population cross mating. Populations of UV-light-induced yeast mutants more tolerant than the wild type to hardwood spent sulfite liquor (HWSSL) were first isolated and then recursively mated and enriched for more-tolerant populations. After five rounds of genome shuffling, three strains were isolated that were able to grow on undiluted HWSSL and to support efficient ethanol production from the sugars therein for prolonged fermentation of HWSSL. Analyses showed that greater HWSSL tolerance is associated with improved viability in the presence of salt, sorbitol, peroxide, and acetic acid. Our results showed that evolutionary engineering through genome shuffling will yield robust yeasts capable of fermenting the sugars present in HWSSL, which is a complex substrate containing multiple sources of inhibitors. These strains may not be obtainable through classical evolutionary engineering and can serve as a model for further understanding of the mechanism behind simultaneous tolerance to multiple inhibitors.
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Identification of novel genes responsible for ethanol and/or thermotolerance by transposon mutagenesis in Saccharomyces cerevisiae. Appl Microbiol Biotechnol 2011; 91:1159-72. [PMID: 21556919 DOI: 10.1007/s00253-011-3298-z] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2010] [Revised: 03/29/2011] [Accepted: 03/31/2011] [Indexed: 10/18/2022]
Abstract
Saccharomyces cerevisiae strains tolerant to ethanol and heat stresses are important for industrial ethanol production. In this study, five strains (Tn 1-5) tolerant to up to 15% ethanol were isolated by screening a transposon-mediated mutant library. Two of them displayed tolerance to heat (42 °C). The determination of transposon insertion sites and Northern blot analysis identified seven putative genes (CMP2, IMD4, SSK2, PPG1, DLD3, PAM1, and MSN2) and revealed simultaneous down-regulations of CMP2 and IMD4, and SSK2 and PPG1, down-regulation of DLD3, and disruptions of the open reading frame of PAM1 and MSN2, indicating that ethanol and/or heat tolerance can be conferred. Knockout mutants of these seven individual genes were ethanol tolerant and three of them (SSK2, PPG1, and PAM1) were tolerant to heat. Such tolerant phenotypes reverted to sensitive phenotypes by the autologous or overexpression of each gene. Five transposon mutants showed higher ethanol production and grew faster than the control strain when cultured in rich media containing 30% glucose and initial 6% ethanol at 30 °C. Of those, two thermotolerant transposon mutants (Tn 2 and Tn 3) exhibited significantly enhanced growth and ethanol production compared to the control at 42 °C. The genes identified in this study may provide a basis for the application in developing industrial yeast strains.
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Mussatto SI, Dragone G, Guimarães PM, Silva JPA, Carneiro LM, Roberto IC, Vicente A, Domingues L, Teixeira JA. Technological trends, global market, and challenges of bio-ethanol production. Biotechnol Adv 2010; 28:817-30. [DOI: 10.1016/j.biotechadv.2010.07.001] [Citation(s) in RCA: 479] [Impact Index Per Article: 34.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2010] [Accepted: 07/02/2010] [Indexed: 11/27/2022]
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Current awareness on yeast. Yeast 2010. [DOI: 10.1002/yea.1718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
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50
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Adrio JL, Demain AL. Recombinant organisms for production of industrial products. Bioeng Bugs 2009; 1:116-31. [PMID: 21326937 DOI: 10.4161/bbug.1.2.10484] [Citation(s) in RCA: 86] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2009] [Revised: 10/30/2009] [Accepted: 11/02/2009] [Indexed: 11/19/2022] Open
Abstract
A revolution in industrial microbiology was sparked by the discoveries of ther double-stranded structure of DNA and the development of recombinant DNA technology. Traditional industrial microbiology was merged with molecular biology to yield improved recombinant processes for the industrial production of primary and secondary metabolites, protein biopharmaceuticals and industrial enzymes. Novel genetic techniques such as metabolic engineering, combinatorial biosynthesis and molecular breeding techniques and their modifications are contributing greatly to the development of improved industrial processes. In addition, functional genomics, proteomics and metabolomics are being exploited for the discovery of novel valuable small molecules for medicine as well as enzymes for catalysis. The sequencing of industrial microbal genomes is being carried out which bodes well for future process improvement and discovery of new industrial products.
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Affiliation(s)
- Jose-Luis Adrio
- NeuronBioPharma, S.A., Parque Tecnologico de Ciencias de la Salud, Edificio BIC, Armilla, Granada, Spain
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