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Geometry and expression enhance enrichment of functional yeast-displayed ligands via cell panning.

ABSTRACT: Yeast surface display has proven to be an effective tool in the discovery and evolution of ligands with new or improved binding activity. Selections for binding activity are generally carried out using immobilized or fluorescently labeled soluble domains of target molecules such as recombinant ectodomain fragments. While this method typically provides ligands with high affinity and specificity for the soluble molecular target, translation to binding true membrane-bound cellular target is commonly problematic. Direct selections against mammalian cell surfaces can be carried out either exclusively or in combination with soluble target-based selections to further direct towards ligands for genuine cellular target. Using a series of fibronectin domain, affibody, and Gp2 ligands and human cell lines expressing a range of their targets, epidermal growth factor receptor and carcinoembryonic antigen, this study quantitatively identifies the elements that dictate ligand enrichment and yield. Most notably, extended flexible linkers between ligand and yeast enhance enrichment ratios from 1.4?±?0.8 to 62?±?57 for a low-affinity (>600?nM) binder on cells with high target expression and from 14?±?13 to 74?±?25 for a high-affinity binder (2?nM) on cells with medium valency. Inversion of the yeast display fusion from C-terminal display to N-terminal display still enables enrichment albeit with 40-97% reduced efficacy. Collectively, this study further enlightens the conditions-while highlighting new approaches-that yield successful enrichment of yeast-displayed binding ligands via panning on mammalian cells. Biotechnol. Bioeng. 2016;113: 2328-2341. © 2016 Wiley Periodicals, Inc.

SUBMITTER: Stern LA

PROVIDER: S-EPMC5036992 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Geometry and expression enhance enrichment of functional yeast-displayed ligands via cell panning.

Stern Lawrence A LA Schrack Ian A IA Johnson Sadie M SM Deshpande Aakash A Bennett Nathaniel R NR Harasymiw Lauren A LA Gardner Melissa K MK Hackel Benjamin J BJ

Biotechnology and bioengineering 20160630 11

Yeast surface display has proven to be an effective tool in the discovery and evolution of ligands with new or improved binding activity. Selections for binding activity are generally carried out using immobilized or fluorescently labeled soluble domains of target molecules such as recombinant ectodomain fragments. While this method typically provides ligands with high affinity and specificity for the soluble molecular target, translation to binding true membrane-bound cellular target is commonl ...[more]

PMID: 27144954

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Project description:MOTIVATION:Protein-protein interactions (PPIs) are usually modeled as networks. These networks have extensively been studied using graphlets, small induced subgraphs capturing the local wiring patterns around nodes in networks. They revealed that proteins involved in similar functions tend to be similarly wired. However, such simple models can only represent pairwise relationships and cannot fully capture the higher-order organization of protein interactomes, including protein complexes. RESULTS:To model the multi-scale organization of these complex biological systems, we utilize simplicial complexes from computational geometry. The question is how to mine these new representations of protein interactomes to reveal additional biological information. To address this, we define simplets, a generalization of graphlets to simplicial complexes. By using simplets, we define a sensitive measure of similarity between simplicial complex representations that allows for clustering them according to their data types better than clustering them by using other state-of-the-art measures, e.g. spectral distance, or facet distribution distance. We model human and baker's yeast protein interactomes as simplicial complexes that capture PPIs and protein complexes as simplices. On these models, we show that our newly introduced simplet-based methods cluster proteins by function better than the clustering methods that use the standard PPI networks, uncovering the new underlying functional organization of the cell. We demonstrate the existence of the functional geometry in the protein interactome data and the superiority of our simplet-based methods to effectively mine for new biological information hidden in the complexity of the higher-order organization of protein interactomes. AVAILABILITY AND IMPLEMENTATION:Codes and datasets are freely available at http://www0.cs.ucl.ac.uk/staff/natasa/Simplets/. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Dataset Information

Geometry and expression enhance enrichment of functional yeast-displayed ligands via cell panning.

Publications

Geometry and expression enhance enrichment of functional yeast-displayed ligands via cell panning.

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