Tanniche, Imen2020-11-292020-11-292019-06-07vt_gsexam:20311http://hdl.handle.net/10919/100954Metabolic engineering has enabled studying microorganisms by the modification of their genetic material and analysis of their metabolism for the isolation of microbial strains capable of producing high yields of high value chemicals and biofuels. In this research, novel tools were developed to improve genetic engineering of microbial cells. In this matter, λ-PCR (lambda-PCR) was developed enabling the construction of plasmid DNA. This technique allows DNA assembly and manipulation (insertion, substitution and/or deletion) at any location of a vector. λ-PCR addresses the need for an easy, highly-efficient, rapid and inexpensive tool for genetic engineering and overcoming limitations encountered with traditional techniques. Then, novel synthetic small RNA (sRNA) regulators were designed in a cell-free-system (in vitro) in order to modulate protein expression in biosynthetic pathways. The ability of the sRNAs to regulate mRNA expression with statistical significance was demonstrated. Up to 70% decrease in protein expression level was achieved by targeting specific secondary structures of the mRNA with antisense binding regions of the sRNA. Most importantly, a sRNA was identified capable of protein overexpression by up to 65%. An understanding of its mechanism showed that its mRNA target region(s) likely lead to occlusion of RNase E binding. This mechanism was translated for expression of a diaphorase enzyme, which has relevance to synthetic biology and metabolic engineering in in vitro systems. Results were successful, showing a greater than 75% increase in diaphorase expression in a cell-free protein synthesis reaction. Next, Raman spectroscopy was employed as a near real-time method for microbial phenotyping. Here, Raman spectroscopy was used in combination with chemometric analysis methods through RametrixTM Toolboxes to study the effects of environmental conditions (i.e. illumination, glucose, nitrate deprivation, acetate, sodium chloride and magnesium sulfate) on the phenotypic response of the cyanobacterium Synechocystis sp. PCC6803. The RametrixTM LITE Toolbox for MATLAB® enabled processing of Raman spectra and application of principal component analysis (PCA) and discriminant analysis of principal components (DAPC). Two studies were performed. PCA and DAPC produces distinct clustering of Raman spectra, representing multiple Synechocystis phenotypes, based on the (i) presence of glucose in the growth medium, (ii) illumination, (iii) nitrate limitation, and (iv) throughout a circadian rhythm growth cycle, in the first study. The second study focused on the phenotypic response based on (i) growth in presence of acetate, (ii) presence of high concentrations of sodium chloride and (iii) magnesium sulfate starvation. RametrixTM PRO was applied for the validation of the DAPC models through leave-one-out method that allowed calculation of prediction accuracy, sensitivity and selectivity for an unkown Raman spectrum. Statistical tests (ANOVA and pairwise comparison) were performed on Raman spectra to identify statistically relevant changes in Synechocystis phenotypes. Next, comparison between Raman data and standardized analytical methods (GF-FID, UPLC, spectrometric assays) was established. Overall, good correlation were obtained (R > 0.7). Finally, genomic DNA libraries were enriched to isolate a deoxynivalenol detoxifying enzyme. To do this, library fragments from microorganisms was generated through oligonucleotide primed polymerase chain reaction (DOP-PCR) and transformed in a DON-sensitive yeast strain. Rounds of subculture were performed in the presence of DON and ferulic acid in order to isolate a strain capable of enzymatic degradation of DON.ETDenIn CopyrightLambda-PCRDNA assemblysynthetic small RNAcell-free-systemRaman spectroscopyRametrixTMphenotypic responseexternal stimulimetagenomic libraryDissertation