Binding Group - Finding novel fabric binding peptides

Goals

• To discover short peptide sequences that allow enzyme-degrading peptides to bind to fabrics in order to concentrate them and increase their activity.

Methods

• Phage display
• Bioinformatic analysis
• Quantitative ELISA

Results

• Isolated XX short peptides that bind cotton, linen, wool, polyester or silk.
• Discovered sequence motifs
• Quantified binding constants of 7 peptides for 5 fabrics with quantitative ELISA.

BioBricks

• BioBrick 1
• BioBrick 2
• BioBrick 3

Abstract

In this sub-project we develop Fabric Binding Domains (FBDs), short peptide sequences capable of binding to fabric samples. Results from the Modeling Group suggest that the addition of an FBD with optimal affinity can concentrate an enzyme near the fabric surface and therefore increase stain-degrading enzymatic activity. Using the method of phage display, we isolated XX short peptides with affinity for cotton, linen, wool, polyester or silk. Bioinformatic analysis identified sequence motifs and biophysical features associated with binding to each fabric, or nonspecific binding to several fabrics. Seven peptides were selected for further analysis by quantitative ELISA, to determine their exact binding constant for each of the five fabrics. The peptides discovered by the Biding Group were passed to the Enzyme Group, where they were used to target GFP and stain-degrading enzymes to wine-stained fabric samples.

Motivation and Background

Classical biochemistry studies the behavior of enzymes in well-mixed solutions with simple, mass-action kinetics. However, most chemical systems in the real world are not well mixed. Living cells in particular have a detailed spatial structure, and cells have developed strategies to maximize enzyme performance in a structured environment (Sweetlove, 2013). Many natural metabolic pathways are structured as metabolons, multi-enzyme complexes in which pathway intermediates are physically channeled from one enzyme to the next.
In recent years, synthetic biologists have created novel metabolic scaffolds to adapt this strategy to engineered metabolic pathways(Pröschel, 2015). The result has been significantly improved pathway performance: increased reaction rates, fewer side reactions, and better control of metabolic intermediates that may be unstable or toxic. Different mechanisms contribute to the improvement depending on the biochemical details of the scaffolded enzymes(Lee, 2012). However, many models emphasize the ability of enzymatic scaffolding to increase the effective concentration of enzymes and substrates by constraining them to the same physical space.

We reasoned that the activity stain-degrading enzymes might also be enhanced by physically linking them to the fabric surface. Our initial intuitions were confirmed and refined by results from the Modeling Group. In fact, our models predict that optimal enzyme performance will be achieved at intermediate binding affinities. At low affinity, enzymes are primarily found in solution and away from the stain. But at extremely high affinity, enzymes are primarily bound to unstained fabric and also unable to reach the stain. Therefore, we sought to prepare a library of fabric binding domains, allowing us to optimize the binding affinity separately for each enzyme, fabric and application.

To identify these Fabric Binding Domains we used the strategy of phage display. In this technique, large libraries of randomized amino acid sequences are displayed by genetically fusing them to phage coat proteins oriented toward the external environment. The phage library is panned against a specific binding target by mixing them and allowing them to reach binding equilibrium. Common targets for phage display libraries include protein antigens and DNA sequences. Some of the randomized peptides displayed on the surface of the phage may become bound to the target while unbound phage are removed by wash steps. The population of bound phage can be then be recovered, amplified and further enriched by additional rounds of panning. Because the randomized amino acid library is genetically encoded, individual phage clones can then be isolated and sequenced to identify high affinity peptides.

Finally we quantified the binding affinity of specific peptide sequences using colorimetric ELISA. In this technique, a specific phage clone is bound to its high-affinity target and then washed a defined number of times. A primary antibody is introduced to recognize the phage, then a secondary antibody is bound carrying Horse Radish Peroxidase, an enzyme that allows a specific colorimetric reading. By quantifying the number of phage that remain bound after each wash, we can determine the precise binding constant.

References

• Sweetlove, L. J., & Fernie, A. R. (2013). The Spatial Organization of Metabolism Within the Plant Cell. Annual Review of Plant Biology, 64(1), 723–746. http://doi.org/10.1146/annurev-arplant-050312-120233
• Lee, H., DeLoache, W. C., & Dueber, J. E. (2012). Spatial organization of enzymes for metabolic engineering. Metabolic Engineering, 14(3), 242–251.
• Pröschel, M., Detsch, R., Boccaccini, A. R., & Sonnewald, U. (2015). Engineering of Metabolic Pathways by Artificial Enzyme Channels. Frontiers in Bioengineering and Biotechnology, 3(Pt 5), 123–13.