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An Image-Analysis-Based Method for the Prediction of Recombinant Protein Fiber Tensile Strength
Silk fibers derived from the cocoon of silk moths and the wide range of silks produced by spiders exhibit an array of features, such as extraordinary tensile strength, elasticity, and adhesive properties. The functional features and mechanical properties can be derived from the structural compositio...
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Published in: | Materials 2022-01, Vol.15 (3), p.708 |
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description | Silk fibers derived from the cocoon of silk moths and the wide range of silks produced by spiders exhibit an array of features, such as extraordinary tensile strength, elasticity, and adhesive properties. The functional features and mechanical properties can be derived from the structural composition and organization of the silk fibers. Artificial recombinant protein fibers based on engineered spider silk proteins have been successfully made previously and represent a promising way towards the large-scale production of fibers with predesigned features. However, for the production and use of protein fibers, there is a need for reliable objective quality control procedures that could be automated and that do not destroy the fibers in the process. Furthermore, there is still a lack of understanding the specifics of how the structural composition and organization relate to the ultimate function of silk-like fibers. In this study, we develop a new method for the categorization of protein fibers that enabled a highly accurate prediction of fiber tensile strength. Based on the use of a common light microscope equipped with polarizers together with image analysis for the precise determination of fiber morphology and optical properties, this represents an easy-to-use, objective non-destructive quality control process for protein fiber manufacturing and provides further insights into the link between the supramolecular organization and mechanical functionality of protein fibers. |
doi_str_mv | 10.3390/ma15030708 |
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The functional features and mechanical properties can be derived from the structural composition and organization of the silk fibers. Artificial recombinant protein fibers based on engineered spider silk proteins have been successfully made previously and represent a promising way towards the large-scale production of fibers with predesigned features. However, for the production and use of protein fibers, there is a need for reliable objective quality control procedures that could be automated and that do not destroy the fibers in the process. Furthermore, there is still a lack of understanding the specifics of how the structural composition and organization relate to the ultimate function of silk-like fibers. In this study, we develop a new method for the categorization of protein fibers that enabled a highly accurate prediction of fiber tensile strength. Based on the use of a common light microscope equipped with polarizers together with image analysis for the precise determination of fiber morphology and optical properties, this represents an easy-to-use, objective non-destructive quality control process for protein fiber manufacturing and provides further insights into the link between the supramolecular organization and mechanical functionality of protein fibers.</description><identifier>ISSN: 1996-1944</identifier><identifier>EISSN: 1996-1944</identifier><identifier>DOI: 10.3390/ma15030708</identifier><identifier>PMID: 35160653</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Adhesive strength ; Biofysik ; Biophysics ; Composition ; Fibers ; Image analysis ; Light ; Mechanical properties ; Microscopy ; Morphology ; Optical properties ; Polarizers ; prediction ; protein fibers ; Proteins ; Quality control ; Silk ; Software ; spider silk ; Spiders ; structure-function relationship ; Tensile strength</subject><ispartof>Materials, 2022-01, Vol.15 (3), p.708</ispartof><rights>2022 by the authors. 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subjects | Adhesive strength Biofysik Biophysics Composition Fibers Image analysis Light Mechanical properties Microscopy Morphology Optical properties Polarizers prediction protein fibers Proteins Quality control Silk Software spider silk Spiders structure-function relationship Tensile strength |
title | An Image-Analysis-Based Method for the Prediction of Recombinant Protein Fiber Tensile Strength |
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