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Expression Vector Optimization

Dec 21, 2019 | Insights

In order to optimize an expression vector optimization it is necessary to properly balance transcription, translation, and plasmid copy number. Maximizing the yield of a biomanufaturing process requires to finely tune these control parameters.

Development of a Proprietary Expression Vector

Problem

Goal: Optimize a bacterial expression vector to maximize the yield of a recombinant protein manufacturing process.

Problem:  Client observed that increasing all control parameters (transcription, translation, plasmid copy number) resulted in a fitness penalty and misfolding of the recombinant protein reducing the yield of the manufacturing process. The client was unsure how to balance transcription, translation, and plasmid copy number to maximize the yield of the biomanufacturing process. Client did not have experience designing and assembling expression vectors.

They needed help to design and execute a research project to optimize their expression vector.

Solution

Using the GenoFAB platform, we worked with the client to:

  • Design
    • Fully annotated minimal vector sequence designed to facilitate assembly operations including promoters for antibiotic resistance gene to finely tune the expression of the selection marker.
    • Generated a library of 48 plasmids using GenoCAD to perform a proof of concept experiment.
    • Minimal set of synthetic DNA fragments to be used to recreate the 48 plasmids included in the experiment minimizing the gene synthesis costs.
    • Using GenoCAM, produced 96 primers with overhangs to amplify synthetic DNA fragments to produce overlapping PCR products suitable for Gibson assembly.
  • Optimize and standardize workflows
    • Plasmid assembly process for speed, stability, and reproducibility prior to scale up.
    • Creation of experiment template using GenoFAB electronic lab notebook.
  • Automate workflows
    • Preparation of assembly reactions by generating pipetting instructions to prepare PCR and Gibson assembly reactions using data from LIMS.
    • Generation of barcode labels and uploading of data in Excel spreadsheets.
  • Manage data
    • Data by creating a model to capture all vector assembly samples in GenoFAB’s LIMS.
    • Data by assembling lllumina reads in GenoCAM and comparing them to the plasmid reference sequence.
    • Data by providing custom database to import data from the plate imager.
    • Results by developing a custom script to connect phenotypic data in the custom database and sample data in the LIMS to estimate protein expression for each of the 48 plasmids in the library.
    • Results by developing a custom script to determine how the different control parameters (origin of replication, promoter controlling the selection marker, and promoter controlling the gene of interest) influenced the yield of recombinant protein expression.

Results

Results from this experiment led to a follow-up project to design a next generation expression vector that client intends to patent. The new proprietary expression vector gave the client company a competitive advantage.

Do you need help designing your own proprietary vectors? Find out about our processes.

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