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Optimizing Recombinant Protein Production for Domain Antibodies: Proof-of-Concept

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Recent studies in traumatic brain injury (TBI) have found a temporal window where therapeutics on the nanometer scale can cross the blood-brain barrier and enter the parenchyma. Developing protein-based therapeutics is attractive for a number of reasons, yet, the production

Recent studies in traumatic brain injury (TBI) have found a temporal window where therapeutics on the nanometer scale can cross the blood-brain barrier and enter the parenchyma. Developing protein-based therapeutics is attractive for a number of reasons, yet, the production pipeline for high yield and consistent bioactive recombinant proteins remains a major obstacle. Previous studies for recombinant protein production has utilized gram-negative hosts such as Escherichia coli (E. coli) due to its well-established genetics and fast growth for recombinant protein production. However, using gram-negative hosts require lysis that calls for additional optimization and also introduces endotoxins and proteases that contribute to protein degradation. This project directly addressed this issue and evaluated the potential to use a gram-positive host such as Brevibacillus choshinensis (Brevi) which does not require lysis as the proteins are expressed directly into the supernatant. This host was utilized to produce variants of Stock 11 (S11) protein as a proof-of-concept towards this methodology. Variants of S11 were synthesized using different restriction enzymes which will alter the location of protein tags that may affect production or purification. Factors such as incubation time, incubation temperature, and media were optimized for each variant of S11 using a robust design of experiments. All variants of S11 were grown using optimized parameters prior to purification via affinity chromatography. Results showed the efficiency of using Brevi as a potential host for domain antibody production in the Stabenfeldt lab. Future aims will focus on troubleshooting the purification process to optimize the protein production pipeline.

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2019-05

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Engineering of Synthetic DNA/RNA Modules for Manipulating Gene Expression and Circuit Dynamics

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Gene circuit engineering facilitates the discovery and understanding of fundamental biology and has been widely used in various biological applications. In synthetic biology, gene circuits are often constructed by two main strategies: either monocistronic or polycistronic constructions. The Latter architecture

Gene circuit engineering facilitates the discovery and understanding of fundamental biology and has been widely used in various biological applications. In synthetic biology, gene circuits are often constructed by two main strategies: either monocistronic or polycistronic constructions. The Latter architecture can be commonly found in prokaryotes, eukaryotes, and viruses and has been largely applied in gene circuit engineering. In this work, the effect of adjacent genes and noncoding regions are systematically investigated through the construction of batteries of gene circuits in diverse scenarios. Data-driven analysis yields a protein expression metric that strongly correlates with the features of adjacent transcriptional regions (ATRs). This novel mathematical tool helps the guide for circuit construction and has the implication for the design of synthetic ATRs to tune gene expression, illustrating its potential to facilitate engineering complex gene networks. The ability to tune RNA dynamics is greatly needed for biotech applications, including therapeutics and diagnostics. Diverse methods have been developed to tune gene expression through transcriptional or translational manipulation. Control of RNA stability/degradation is often overlooked and can be the lightweight alternative to regulate protein yields. To further extend the utility of engineered ATRs to regulate gene expression, a library of RNA modules named degradation-tuning RNAs (dtRNAs) are designed with the ability to form specific 5’ secondary structures prior to RBS. These modules can modulate transcript stability while having a minimal interference on translation initiation. Optimization of their functional structural features enables gene expression level to be tuned over a wide dynamic range. These engineered dtRNAs are capable of regulating gene circuit dynamics as well as noncoding RNA levels and can be further expanded into cell-free system for gene expression control in vitro. Finally, integrating dtRNA with synthetic toehold sensor enables improved paper-based viral diagnostics, illustrating the potential of using synthetic dtRNAs for biomedical applications.

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2020