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 Binding 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 of 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 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.

Results

Our phage display experiments were performed with the commercial Ph.D.-7 Phage Display Peptide Library (NEB # E8100S). This library consists 100 copies each of 10^9 phages expressing a randomized 7-mer peptide fused to the phage N-terminal pIII coat protein. The displayed peptide is separated by a short Gly-Gly-Gly-Ser linker to minimize interactions between the displayed peptide and the phage itself. The supplier provides extensive documentation on the diversity and composition of the initial library, allowing comparisons to be made to the phage population after panning.

Panning against cotton, linen, wool, polyester and silk

The phage library was panned against fabric samples of cotton, linen, wool, polyester and silk. The cycle of phage binding, elution, and amplification was repeated three times for each fabric. Following enrichment, individual clones were isolated and sequenced to determine the sequence of their displayed peptide.

Analysis of the isolated clones

DNA was extracted from the phages and then sequenced. Sequences were analyzed using Geneious. The randomized region was found by searching for the linker region and the end the peptide leader sequence. The 21 nucleotides were then reverse complemented and translated.

Methods

Selection of fabric samples for panning

• Cotton was obtained from Khadi and Co - Bess Nielsen - Hand Woven, 100% cotton.
  
• Wool and Linen was obtained from Dharma trading and co. Wool- #PWFC, Linen- #LIN21
  
• A square of 1cm x 1cm was used (total surface: 2 cm² counting both sides)
  
• Silk used: Thread 1003 Au ver a Soie - Colour: Crème (Cream) - 100% Silk - Length: 50 cm - Weight: 16.5mg.
  
• Polyester used: Polyester thread Mediac Ref: 960 - Colour: 400 - 100% Polyester - Length: 50cm - Weight: 16mg.
  

Preparation of fabric samples for panning

Cotton was boiled in soda ash (Na2CO3) and then washed with water- till the pH is neutral- prior to panning to remove coatings, preservatives or other treatments that may have been applied in the factory.
Rest of the fabrics were washed with ethanol and water.

Detailed protocol for phage display

Phage display describes a selection technique in which phages with genetic material encoding variants of peptide sequences express these peptides on the protein coat. And based on the binding affinity of these peptides to a given target molecule by an in vitro selection process called panning, selective phages can be separated and enriched. We adapted the NEB protocol to accommodate our target, so panning is carried out by incubating a library of phage-displayed peptides (2*10^11 phages) with our fabric of choice in a micro centrifuge tube, washing away the unbound phage, and eluting the specifically bound phage-

• The 2cm*0.5cm washed fabric was blocked overnight with 0.1M NaHCO3,0.5% BSA buffer.
• 10 µl of phage from NEB(10^13 pfu/ml) was mixed with 250µl of TBS to give a concentration of 2*10^11 phage. The blocked fabric was incubated for one hour in the phage mixture with gentle agitation.This process is called panning.
• The fabric was washed vigourously 20 times in a 0.1% TBST bath.
• Fabric was eluted with 0.2 M Glycine-HCl (pH 2.2), 1 mg/ml BSA, this distrupts all nonspecific binding interactions and neutralized with 1 M Tris-HCl, pH 9.1.
• To amplify the phages the eluate is inoculated in ER2738 culture, incubated for 4.5hrs and is then mixed with 20% PEG/NaCl, incubated overnight to precipitate the phages.
• Precipitated phages were then resuspended in TBS. This was titred to calculate the input for next round of panning.
• The phages from Round 1 was taken through additional binding/amplification cycles to enrich the pool in favor of binding sequences. After 3–4 rounds of panning, individual clones will be characterized by DNA sequencing and later ELISA

Sequence similarity was calculated as BLOSUM. Trees were made using Geneious with nearest neighbor joining.

Sequence clustering analysis

Binding quantification with ELISA

To eliminate the artifacts of the panning process and to quantify the binding affinities we performed phage ELISA.

• In this procedure a microcentrifuge tube with our target (fabric)is is blocked overnight
• Each purified phage clone is applied to control(tubes without target) and tubes with target starting with 10^12 virions in the first tube of a row and ending with 2 x 10^4 virions in the 12th tube.
• The tubes are washed with increasing volume of wash buffer to remove unbound phages.
• Bound phage is then detected with an anti-M13 antibody (anti-M13-HRP conjugate, GE Healthcare #27-9421-01).
• ABTS (Sigma, cat. # A-1888) peroxidase substrate reacts with HRP to yield a measurable green end product which is read at 410nm.
  

Note: 10^11 phages per tube corresponds to a phage concentration of only 1.6 nM. At this concentration, an unambiguously positive ELISA signal can only be observed if the binding affinity is in the micromolar range or better. The iterative nature of phage selection permits identification of ligands with a broad range of affinities, from sub-nM to 1 mM, so lower affinity ligands will not show a positive ELISA signal.
We picked one fabric binding domain - FBD9 and one fabric - cotton to do a quantitative ELISA which would allow us to calculate the binding constant.
The assay involved increasing the wash volume from 1ml to 10ml and also wash buffer - 1% Tween20, 1% Triton X100, 1% SDS.

Attributions

This project was done mostly by Shruthi and Thomas. We would like to thank Clément Nizak and the Nizak lab for help in designing the phage display protocol.

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.
• 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.