Title page for ETD etd-12162011-145023


Type of Document Master's Thesis
Author Yue, Yang
Author's Email Address yyang09@vt.edu
URN etd-12162011-145023
Title The Development of a Thermodynamic Model for Antisense RNA Design and an Electro-transformation Protocol to Introduce Auxotrophic Genes for Enhancing Eicosapentaenoic Acid Yield from Pythium irregulare
Degree Master of Engineering
Department Biological Systems Engineering
Advisory Committee
Advisor Name Title
Senger, Ryan S. Committee Chair
Keywords
  • thermodynamic model
  • fermentation and analysis
  • eicosapentaenoic acid(EPA)
  • antisense RNA
Date of Defense 2011-12-07
Availability restricted
Abstract
Eicosapentaenoic acid (EPA, C20:5, n-3) is a long chain crucial unsaturated fatty acid, essential for the regulation of critical biological functions in humans. Its benefits include the therapeutic treatment of cardiovascular disease, schizophrenia and Alzheimer’s disease. The fungus Pythium irregulare (ATCC 10951) has great potential as a natural EPA producer. In this study, the electroporation conditions for P. irregulare were determined. The auxotrophic selectable genes ura, trp and his were respectively cloned into the plasmid pESC to construct shuttle vectors. Electroporation with 2.0kV and a 0.2cm cuvette was applied as the most effective condition for heterogeneous genes transformation. The yield and content of EPA and other components of total fatty acids (TFA) were further determined by the FAME approach with GC, as well as the analysis of biomass. The EPA content in P. irregulare with heterologous pESC-TRP vector reached 16.68 mg/g if cultured in auxotrophic medium, which showed a 52.33% increase compared to the wild-type P. irregulare. The maximum of EPA yield was 98.52 mg/L from P. irregulare containing the pESC-URA plasmid, a 32.28% increase over the wild-type. However, the maximum cell dried weight of these two organisms were respectively 6.13g/L and 5.3g/L, significantly less than the 6.80g/L of the wild-type. Not only was a feasible approach detected to electro-transform and increase the EPA yield of P. irregulare, this study also inferred that ω-6 route was mainly involved in the EPA biosynthesis in this organism.

An antisense RNA (asRNA) thermodynamic model was developed to design new asRNA constructs capable of fine-tuning gene expression knockdown. The asRNA technology is now identified as an effective and specific method for regulating microbial gene expression at the posttranscriptional level. This is done by targeting mRNA molecules. Although the study of regulation by small RNAs is advanced in eukaryotes, the regulation of expression through artificially introducing antisense oligodeoxynucleotides into host is still being developed in prokaryotes. To study the thermodynamics of asRNA and mRNA binding, (i) the fluorescence protein genes GFP and mCherry were separately cloned into the common pUC19 vector and (ii) antisense GFP and antisense mCherry DNA fragments were randomly amplified and inserted into the constructed plasmid under the control of an additional plac promoter and terminator. The expression level of fluorescence reporter proteins was determined by plate reader in this combinatorial study. A thermodynamic model to describe the relationship between asRNA binding and observed expression level was created. The study indicates two factors that minimum binding energy of the asRNA-mRNA complex and the percentage of asRNA binding mRNA were crucial for regulating the expression level. The correlation relationship between gene expression level and binding percentage multiplied by the minimum binding energy was found to show a good correlation between the thermodynamic parameters and the observed level of gene expression. The model has the potential to predict the sequence of asRNA and the approach will ultimately be applied to cyanobacteria to increase lipids production. Here, the long-term approach is to build metabolic switches from asRNA that can turn “on/off” various cellular programs and metabolic pathways at will in a fine-tuned manner. This will allow engineers to control metabolic activity in response to reactor conditions.

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