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Mar 15, 2012 (Vol. 32, No. 6)

Harnessing Innovation to Improve Expression Systems

  • Technical advances in the use of protein-expression systems have enabled scaled production of membrane proteins and other difficult to express proteins. These advances have also helped preserve the structure and function of the expressed proteins.

    Shuguang Zhang, Ph.D., associate director of the Center for Biomedical Engineering at MIT, has found that the use of short peptide surfactants in commercial E. coli cell-free systems facilitates the rapid production of membrane proteins.

    GPCRs, the most difficult integral membrane proteins to produce, can be produced in milligram quantities when the right surfactant is added to the cell-free system. The soluble GPCRs that Dr. Zhang’s team has produced show a-helical secondary structures, which suggest proper folding; ligand binding studies have confirmed the maintenance of biological function.

    “I am convinced that the use of short, simple peptide surfactants is absolutely the key for successful production of membrane proteins in cell-free systems,” he says. “Further, the use of cell-free systems allows for industrial-scale standardization of protein production. We have demonstrated its utility on GPCRs. If we can just reduce the cost 10–20 fold in the next decade, I have no doubt you’ll see an increase in its use for protein production.”

    The benefit of using cell-free systems is the ease of use and the ability to add components to promote protein production and stability. These cell-free systems can be maintained for a long time, though they are not amenable to repeat production.

    As for the addition of peptide surfactants, it is essential to screen different surfactants to ensure matching with each individual membrane protein for optimal production. The peptide surfactants that have been used are designed with a hydrophilic head (1–2 residues) and a hydrophobic tail (3–6 residues). They are usually 2–3 nm in length, their ionic character and strength can be controlled by selection of the intervening residues.

    The surfactants have a tendency to self-assemble to form membrane-like environments that provide stability for the membrane proteins, even though the mechanism remains unclear.

    Joining Dr. Zhang as a presenter at the upcoming “PEGS” conference in Boston will be Mark Welch, Ph.D., director of gene design at DNA2.0.

  • Click Image To Enlarge +
    Expression of polymerase variants (red squares) and scFv antibody variants (blue diamonds): Each point shows data from a different codon bias. Genes designed using DNA2.0’s advanced algorithms are shown in green. Black symbols show the two major algorithms used by alternate approaches: matching the E. coli genome bias (filled black symbols) or matching the bias found in highly expressed genes (open black symbols).

    DNA2.0’s custom gene design and synthesis service enables customers to obtain optimal protein expression for their gene of interest, according to Dr. Welch. The company is guided by informatics and experimental studies of the effect of gene usage on heterologous protein expression from different expression and production hosts (bacterial, yeast, and mammalian cells). From this analysis, the company has developed robust algorithms that predict optimal gene sequences that will provide abundant protein yields.

    At present, DNA2.0 has turned its attention to the application of these tools for optimal production of pharmaceutical target proteins in mammalian hosts. “We have developed solid algorithms for production of a variety of proteins in bacteria and yeast systems,” Dr. Welch explained. “We are now focused on building that same level of knowledge in mammalian cell systems.”

    Working with an academic partner, DNA2.0 is also exploring the optimization of protein expression of difficult to express membrane proteins as well as the effects of gene sequence on expression level and localization in differentiated mammalian tissues.

    Dr. Welch will also talk about Infologs™, non-natural gene variants that are designed through informatics to capture maximal structure/function correlations in the biological space of interest. DNA2.0’s research demonstrates how the technique leads to uniform sampling, systemic variance, and unrestricted information-rich results.


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