Bioremediation of elastane within the textile industry

Lead Research Organisation: Aston University
Department Name: College of Engineering and Physical Sci

Abstract

In 2019, the global textile market reached 111 million tons (mt), with less than 1% coming from textile-to-textile recycling (Exchange, 2020). Synthetic fibres and polymer blends are often used, with 63% of the current market being comprised of petroleum-based virgin fibres (Borneman, 2015). Recycling of these polymer blends and petroleum-based fibres is difficult, and lack of component recovery means a large number of these materials end up in landfills or incinerators. Reaching a circular textile economy by recovering individual components of these non-renewable polymer blends, with emphasis on achieving the same properties (e.g., thermal and tensile strength) as the respective starting materials, is imperative for sustainability and reduction of environmental impact (Jönsson et al., 2021).
Elastane, a poly(urethane-urea) copolymer, is often used in textile blends to increase elasticity and tensile strength (with e.g., denim, cotton, or polyamide) (AK and Bansal, 2018; Dhouib, 2006). Approximately 20% of recyclable textile waste contains elastane (Jönsson et al., 2021). Current separation methods fail to fully separate elastane for reprocessing. For example, melt filtration and melt spinning are not sufficient to separate elastane from polyamide (PA), as the elastane degrades and passes through filters. Also, mechanical separation results in elastane disappearing from the tearing machine in PA fabric with high elastane content (~22%), and fails to fully separate PA fabric with low elastane content (~5%). Therefore, reprocessing cannot continue as elastane acts as a contaminant (Jönsson et al., 2021). A method for separating elastane and achieving the same properties as the virgin fibre does not currently exist.
The aim of this research is to develop a method to enzymatically degrade elastane for the de-polymerisation of textiles, whilst investigating chemical/thermal pre-treatment, and optimising biotransformation conditions affecting conversion yields - for future application of recycling elastane at an industrial scale.
Research Plan/Methods:
Using heat shock, plasmids encoding for desired enzymes will be inserted into various types of bacteria (e.g., E. coli) and yeast (e.g., C. cladosporioides), then produced on agar (e.g., LB for E. coli) with antibiotic selection markers (e.g., neomycin) to identify the most suitable bacterial strain for enzyme production. To extract the enzymes, cell lysis by French press will be carried out. For purification, the target enzymes could be His-tagged and then purified with a nickel-resin in an immobilised affinity purification column (eluted with imidazole). Enzyme-linked immunosorbent assays (ELISAs) will confirm production of target enzymes - with quantitative ELISA assays being deployed for identifying the most optimal microbial strains and production conditions.
We will employ colorimetric assays to monitor the enzyme kinetics of de-polymerisation (e.g., ammonia release assays for the breakdown of polyurea by urease). Due to the novel nature of elastane-degrading enzymes on polymers, colorimetric assays may not be available. For this, HPLC (preliminary) and LC-MS (further analysis) will be used to identify substrate degradation and product formation. This analysis will also provide insight into reaction intermediates, allowing for the study of the de-polymerisation pathway mechanism. Furthermore, identification of de-polymerisation products allows us to explore further applications of by-products.
However, synthetic polymers are strongly resistant to depolymerisation due to shielding of reactive bonds by a strong secondary structure. Pre-treatment strategies (thermal, chemical, and UV) oxidise and reduce hydrophobicity of the polymer's surface, supporting the growth of a microbial film (Arkatkar et al., 2009). Pre-treatments, such as liquid nitrogen for poly(ethylene terephthalate), have been shown to increase enzymatic rate by two orders of magnitude (Tournier et al., 2020

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/T518128/1 01/10/2020 30/09/2025
2746959 Studentship EP/T518128/1 01/10/2022 31/03/2026 Lewis Yandle