Analysis Of Ethanol Tolerance And Metabolic Engineering For Improved Fermentation In Saccharomyces Cerevisiae

Saccharomyces cerevisiae, as the most human related species, has quite extensive applications during the history of human beings. Very high gravity fermentation (VHGF) can reach a relative high ethanol concentration in the same equipment and time scale, making the cost down, VHGF has recently draw brewer's attention due to its advantage of energy, laboring and space saving. However, high concentrations of carbohydrate initially in VHGF can bring osmotic pressure to cells inhibiting its specific growth rate and production activity. Besides, the gradual increased ethanol produced along fermentation affected cell growth and even made fermentation stuck. Given this, it is requisite that yeast strains used for VHGF should possess superior tolerance properties.Although many efforts have been devoted to elicit these properties, the adaptation and response mechanisms to stresses still have not been fully understood till now. Meanwhile, industrial diploid strains possess different genetic background and higher stress resistance than the laboratory haploid strains. It is difficult to enhance yeast tolerance only by modifying one or two target genes, especially for industrial strains with naturally sophisticated ethanol tolerance and productivity.Transcription initiation by RNA polymerase II involves the assembly of general transcription factors on the core promoter to form a preinitiation complex (PIC), which contains several General/basal transcription factors (GTF's), named TFâ…¡A,TFâ…¡B,TFâ…¡C,TFâ…¡D,TFâ…¡Få’ŒTFâ…¡H. All of them constitute a complex of about 2MDa. TFIID is a multi-subunit complex consisting of TBP and a set of TBP-associated factors (TAFs). The first step in PIC assembly is binding of the TATA-box-binding protein (TBP) or TFIID to the TATA box. Transcriptional activators bind to specific cis-acting promoter elements within upstream activating sequences (UASs)/enhancers and stimulate PIC assembly through a mechanism thought to involve direct interactions with one or more components of the transcription machinery. The communication between the enhancer-bound activators and the basal transcription machinery depends on a third class of transcription factors, the so-called coactivators. Each gene is controlled by a unique array of binding sites for distinct activators that ensure its expression at the right time and place.The tremendous complexity of dynamic interactions in cellular systems often impedes practical applications of metabolic engineering that are largely based on available molecular or functional knowledge. Global transcription machinery engineering (gTME) is a new cellular engineering concept advocated by Alper and Stephanopoulos, which aims to modify the transcription factor behavior to reprogram a series of gene transcription. It enables multiple, simultaneous perturbations at genomic level.In contrast, evolutionary engineering follows nature's'engineering' principle by variation and selection. Thus, it is a complementary strategy that offers compelling scientific and applied advantages for strain development and process optimization, provided a desired phenotype is amenable to direct or indirect selection. In addition to simple empirical strain development by random mutation and direct selection on plates, evolutionary engineering also encompasses recombination and continuous evolution of large populations over many generations. Two distinct evolutionary engineering applications are likely to gain more relevance in the future:first, as an integral component in metabolic engineering of strains with improved phenotypes, and second, to elucidate the molecular basis of desired phenotypes for subsequent transfer to other hosts. The latter will profit from the broader availability of recently developed methodologies for global response analysis at the genetic and metabolic level. These methodologies facilitate identification of the molecular basis of evolved phenotypes. It is anticipated that, together with novel analytical techniques, bioinformatics, and computer modeling of cellular functions and activities, evolutionary engineering is likely to find its place in the metabolic engineer's toolbox for research and strain development.The major results of the thesis are as follows:gTME was applied in a standard strain by a centromeric plasmid. SPT15-300 was expressed under the control of a constitutive promoter PTEF. Strains expressing SPT15 as control, cell growth phenotype was compared under different combined stress conditions with elevated ethanol/glucose concentrations. To our disappointed, the strain expressed SPT15-300 showed marginally improved. This is likely related to the media containing plenty of nutrition. The impacts of SPT15-300 to yeast exhibited its complexity.While gTME made little sense to standard strains, directed evolution was adopted by guadual increasing ethanol concentration for about 45 days. A mutant holding eleviated ethanol tolerance was obtained, which could grow under media with 8% ethanol, while the control did not grow at all. Following that, serial analysis of gene expression (SAGE) was performed to analysis differential expression genes under YPD containing no or 6% ethanol for the adapted strain and its parent strain. By clustering of these differential expression genes, we got distinct gene clustering modules for each sample, with up-regulated and down-regulated genes in different region. This implied that EA and W303-1A showed differential gene expression module even under no stress condition. Some genes, such as SSA4, OLE1, HXK1, showed constitutive expression in EA. Furthermore, gene expression under ethanol stress for EA and W303-1A also showed diversity.Gene ontology (GO), pathway analysis and protein-protein interaction network were carried out. Genes involved in plasma membrane, cytoplasm, cell wall, nucleolus, mitochondrion, vacuole and proteasome complex all showed differential expression. They participated in protein binding, enzyme regulator activity, ribonuclease activity, and transport, biosynthetic and metabolic proces, oxidative phosphorylation, endocytosis and so on. As for pathway, polyunsaturated fatty acid biosynthesis and amino acid metabolism showed remarkably enriched under ethanol response. Especially, the OLE1 gene,which is vital for polyunsaturated fatty acid biosynthesis, showed up-regulated both under ethanol reponse of W303-1A and under no stress of EA. Genes involved in ribosome protein synthesis were consistent up-regulated in EA under ethanol response, making it more robust under stress. By network analysis, a gene coding protein, HSP82 was significantly interacted, which is consistent with its role in protein network.For the first time, gTME was also applied into the industrial brewer yeast with two steps of homologous recombination without introducing additional exogenous genes or plasmid, which resulting in a similar growth phenotype in the same condition as reported by Baerends et al. However, we found that the fermentation performance of the engineered strain was improved under high gravity conditions.A mutant with excellent ethanol tolerance was obtained. And gene differential expression was carried out by SAGE analysis between the mutant and its parents, which interpreted the molecular mechanism underlining the changes of ethanol tolerance. Combined gTME and directed evolution, the performance was improved distinctly under VHGF. All of these have potential applications both in understanding ethanol tolerance and VHGF.