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Research article - Peer-reviewed, 2022

An Image-Analysis-Based Method for the Prediction of Recombinant Protein Fiber Tensile Strength

Backlund, Fredrik G.; Schmuck, Benjamin; Miranda, Gisele H. B.; Greco, Gabriele; Pugno, Nicola M.; Ryden, Jesper; Rising, Anna;

Abstract

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.

Keywords

spider silk; protein fibers; image analysis; structure-function relationship; prediction; mechanical properties

Published in

Materials

2022, volume: 15, number: 3, article number: 708
Publisher: MDPI

Authors' information

Backlund, Fredrik G.
Karolinska Institutet
Karolinska Institutet
Miranda, Gisele H. B.
Royal Institute of Technology
University of Trento
Swedish University of Agricultural Sciences, Department of Anatomy, Physiology and Biochemistry (AFB)
Pugno, Nicola M.
University of Trento
Pugno, Nicola M.
University of London
Swedish University of Agricultural Sciences, Department of Energy and Technology
Karolinska Institutet
Swedish University of Agricultural Sciences, Department of Anatomy, Physiology and Biochemistry (AFB)

UKÄ Subject classification

Biophysics

Publication Identifiers

DOI: https://doi.org/10.3390/ma15030708

URI (permanent link to this page)

https://res.slu.se/id/publ/116853