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ABSTRACT: The optimization, purification and characterization of bioflocculant produced by Paenibacillus elgii B69 were investigated. The bioflocculant was an exopolysaccharide composed of glucose, glucuronic acid, mannose and xylose. The maximum bioflocculant production was about 25.63g/L achieved with sucrose at 51.35g/L, peptone at 6.78g/L and yeast extract at 0.47g/L optimized by response-surface methodology. In addition, a series of experiments was performed to investigate the flocculation activities towards kaolin clay, dyeing pigment, heavy metal ion, and real wastewater and the result indicated the new bioflocculant had high activities towards all the tested pollutions. These results showed its great potential for water pretreatment used in industry.
Bioresource technology 02/2013; 134C:87-93. · 4.25 Impact Factor
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ABSTRACT: An understanding of the genetic basis underlying the phenotypic variations of yeast strains would guide the breeding of this useful microorganism. Here, comparative functional genomics (CFG) of two bioethanol Saccharomyces cerevisiae strains (YJS329 and ZK2) with different stress tolerances and ethanol fermentation performances were performed. Our analysis indicated that different patterns of gene expression in the central carbon metabolism, antioxidative factors, and membrane compositions of these two strains are the main contributors to their various traits. Some of the differently expressed genes were directly caused by the genomic structural variations between YJS329 and ZK2. Moreover, CFG of these two strains also led to novel insights into the mechanism of stress tolerance in yeast. For example, it was found that more oleic acid in the plasma membrane contributes to the acetic acid tolerance of yeast. Based on the genetic information particular to each strain, strategies to improve their adaptability and ethanol fermentation performances were designed and confirmed. Thus, CFG could not only help reveal basis of phenotypic diversities but also guide the genetic breeding of industrial microorganisms.
Applied Microbiology and Biotechnology 01/2013; · 3.42 Impact Factor
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ABSTRACT: BACKGROUND: Environmental stresses and inhibitors encountered by Saccharomyces cerevisiae strains are the main limiting factors in bioethanol fermentation. Strains with different genetic backgrounds usually show diverse stress tolerance responses. An understanding of the mechanisms underlying these phenotypic diversities within S. cerevisiae populations could guide the construction of strains with desired traits. RESULTS: We explored the genetic characteristics of the bioethanol S. cerevisiae strain YJS329 and elucidated how genetic variations in its genome were correlated with specified traits compared to similar traits in the S288c-derived strain, BYZ1. Karyotypic electrophoresis combined with array-comparative genomic hybridization indicated that YJS329 was a diploid strain with a relatively constant genome as a result of the fewer Ty elements and lack of structural polymorphisms between homologous chromosomes that it contained. By comparing the sequence with the S288c genome, a total of 64,998 SNPs, 7,093 indels and 11 unique genes were identified in the genome of YJS329-derived haploid strain YJSH1 through whole-genome sequencing. Transcription comparison using RNA-Seq identified which of the differentially expressed genes were the main contributors to the phenotypic differences between YJS329 and BYZ1. By combining the results obtained from the genome sequences and the transcriptions, we predicted how the SNPs, indels and chromosomal copy number variations may affect the mRNA expression profiles and phenotypes of the yeast strains. Furthermore, some genetic breeding strategies to improve the adaptabilities of YJS329 were designed and experimentally verified. CONCLUSIONS: Through comparative functional genomic analysis, we have provided some insights into the mechanisms underlying the specific traits of the bioenthanol strain YJS329. The work reported here has not only enriched the available genetic resources of yeast but has also indicated how functional genomic studies can be used to improve genetic breeding in yeast.
BMC Genomics 09/2012; 13(1):479. · 4.07 Impact Factor
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ABSTRACT: To overcome the drawbacks of protoplast fusion in industrial breeding, strain-specific molecular markers were applied to select
hybrids of industrial Saccharomyces cerevisiae strains. Random Amplified Polymorphic DNA (RAPD) analysis was used to generate strain-specific RAPD markers for two industrial
yeast strains, Z8 and Z9. For industrial and technical controls, two RAPD markers with non-coding regions were converted into
stable Sequence Characterized Amplified Region (SCAR) markers. Hybrids of Z8 and Z9 were obtained by protoplast fusion in
combination with SCAR markers and were found to increase ethanol production by 4.3–8.1%. Results suggested that protoplast
fusion could be combined with RAPD-SCAR molecular markers and applied in industrial breeding instead of auxotrophic markers.
KeywordsIndustrial breeding–Molecular marker–Protoplast fusion–
Saccharomyces cerevisiae
World Journal of Microbiology and Biotechnology 04/2012; 27(1):185-188. · 1.53 Impact Factor
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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.
Bioresource technology 03/2012; 108:203-10. · 4.25 Impact Factor
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ABSTRACT: BACKGROUND: During anaerobic bioethanol fermentation of Saccharomyces cerevisiae, the main byproduct glycerol is essential to regulate redox balance (reoxidize NADH to NAD+), which is necessary to maintain cell growth and fermentation. Hetero-expression of a NADP+-dependent glyceraldehydes-3-phosphate dehydrogenase (GAPN) [EC.1.2.1.9] in S. cerevisiae could redirect the carbon flux from glycerol to ethanol involving a net oxidation of NADH. The present study investigates whether combination of GAPN hetero-expression and glycerol exporter Fps1p disruption would result in less glycerol and more ethanol production without affecting growth rate during anaerobic fermentations.RESULTS: The results of anaerobic fermentations showed that the fps1Δ mutant with GAPN (named 4FG) produced 21.47% less glycerol and 9.18% more ethanol compared with a parental strain with a control plasmid, while the rates of growth and fermentation were not changed. Moreover, the engineered strain 4FG yielded less glycerol and acetic acid, and more ethanol than the control, fps1Δ mutant or with GAPN only.CONCLUSIONS: During anaerobic fermentations, hetero-expression of GAPN restored the reduced grow rate of the fps1Δ mutant, and led to less byproducts and more ethanol production. This combination strategy could be used to modulate glycerol metabolism and optimize the anaerobic fermentation of S. cerevisiae. Copyright © 2011 Society of Chemical Industry
Journal of Chemical Technology & Biotechnology 04/2011; 86(9):1205 - 1210. · 2.17 Impact Factor
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ABSTRACT: Acetic acid existing in a culture medium is one of the most limiting constraints in yeast growth and viability during ethanol fermentation. To improve acetic acid tolerance in Saccharomyces cerevisiae strains, a drug resistance marker-aided genome shuffling approach with higher screen efficiency of shuffled mutants was developed in this work. Through two rounds of genome shuffling of ultraviolet mutants derived from the original strain 308, we obtained a shuffled strain YZ2, which shows significantly faster growth and higher cell viability under acetic acid stress. Ethanol production of YZ2 (within 60 h) was 21.6% higher than that of 308 when 0.5% (v/v) acetic acid was added to fermentation medium. Membrane integrity, higher in vivo activity of the H+-ATPase, and lower oxidative damage after acetic acid treatment are the possible reasons for the acetic acid-tolerance phenotype of YZ2. These results indicated that this novel genome shuffling approach is powerful to rapidly improve the complex traits of industrial yeast strains.
Journal of Industrial Microbiology 03/2011; 38(3):415-22. · 1.80 Impact Factor
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ABSTRACT: In this study, a systemic analysis was initially performed to investigate the relationship between fermentation-related stress tolerances and ethanol yield. Based on the results obtained, two elite Saccharomyces cerevisiae strains, Z8 and Z15, with variant phenotypes were chosen to construct strains with improved multi-stress tolerance by genome shuffling in combination with optimized initial selection. After three rounds of genome shuffling, a shuffled strain, YZ1, which surpasses its parent strains in osmotic, heat, and acid tolerances, was obtained. Ethanol yields of YZ1 were 3.11%, 10.31%, and 10.55% higher than those of its parent strains under regular, increased heat, and high gravity fermentation conditions, respectively. YZ1 was applied to bioethanol production at an industrial scale. Results demonstrated that the variant phenotypes from available yeast strains could be used as parent stock for yeast breeding and that the genome shuffling approach is sufficiently powerful in combining suitable phenotypes in a single strain.
Bioresource technology 10/2010; 102(3):3020-7. · 4.25 Impact Factor
