Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/49758
Title: Enhanced Yields and Purity: A Robust Optimization Framework for the Production of Multifunctional Elastin-Like Proteins
Data Creator - person: GEYSMANS, Niels 
VASTMANS, Lotte 
Verstraete, Ruben
Van Ostade, Xaveer
BITO, Virginie 
GRAULUS, Geert-Jan 
Publisher: Open Science Framework
Issue Date: 2026
Abstract: Elastin-Like Proteins (ELP) are highly versatile biomaterials with significant potential in tissue-engineering, due to their design flexibility, mechanical properties and tunable stimuli responsiveness. However, expression conditions reported in literature do not always translate to new ELP fusion proteins. This study establishes a methodology to optimize expression conditions for modular ELP constructs with intermittent peptide domains. Response Surface Methodology is employed to systematically optimize protein expression of three distinct ELP constructs (containing either RGD domains, heparin-binding domains, or a combination thereof) currently being explored in the domain of injectable biomaterials. By combining small-scale expression with western blot densitometry, an accessible workflow is established to systematically optimize expression yields while avoiding extensive sample preparation and limiting the number of experiments. Analysis of the lower critical solution temperature of the ELPs suggests a correlation between the molecular architecture and the observed transition temperature. Furthermore, in vitro biocompatibility analyses confirm high cell viability, validating these modular ELPs as promising candidates for injectable hydrogels.
Research Discipline: Natural sciences > Chemical sciences > Macromolecular and materials chemistry > Synthesis of materials (01040307)
Engineering and technology > Materials engineering > Biomaterials engineering > Biomaterials (02050101)
Keywords: Elastin-like proteins;design-of-experiments;protein expression
DOI: https://doi.org/10.17605/OSF.IO/YCQDV
Source: Open Science Framework. https://doi.org/10.17605/OSF.IO/YCQDV
Publications related to the dataset: https://doi.org/10.1039/d6bm00527f
Publications related to the dataset: http://hdl.handle.net/1942/49723
License: Creative Commons Attribution 4.0 International (CC-BY-4.0)
Access Rights: Open Access
Category: DS
Type: Dataset
Appears in Collections:Datasets

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