Efficient Sorting of Polylactic Acid from Mixed Plastics

Polylactic acid (PLA) is one of the most promising bioplastics and is widely used in various fields such as food packaging, agricultural films, 3D printing, and drug delivery. In order to improve its melt processability, thermal stability and stiffness, PLA is usually mixed with polypropylene (PP). As PLA production continues to increase, there is an urgent need to develop a new recycling process to effectively separate PLA from mixed plastics.

In response to the above scientific problems, researchers have made a breakthrough in the field of plastic sorting and developed for the first time a high-throughput screening system (PLABS) based on a 96-well microplate to improve PLA binding specificity, and applied to engineer material-binding peptides (MBPs) to improve their PLA-binding specificity.

MBP has excellent bonding properties and can be combined with a variety of materials, including polymers such as PP, polystyrene (PS), and polyethylene terephthalate (PET). It has been reported that the stable binding properties of MBP can resist the effects of surfactants and rain washout. MBP has been successfully used to sort microplastics by flow cytometry and promote the enzymatic degradation of PET, polyhydroxyalkanoate (PHA) and other plastics. Knowledge acquisition-oriented directed evolution (KnowVolution) developed by researchers is an advanced protein engineering strategy. Compared with traditional directed evolution methods, KnowVolution is not limited by specific properties and large data sets. KnowVolution combines computer simulations and experiments to minimize experimental workload, rapidly improve protein properties, and simultaneously gain an understanding of the molecular mechanisms of effective mutants. KnowVolution has been widely used to improve protein activity, thermal stability, pH stability, regioselectivity, ionic liquid resistance, and polymer processability. In addition, KnowVolution has been successfully used to enhance the binding properties of MBP to different types of polymers.

In this study, after comparing the binding properties of various MBPs to PLA and PP, the researchers selected Cg-Def for protein engineering to improve its PLA binding specificity. The researchers first developed and verified the PLABS system. This screening system enables the screening and evolution of PLA-specific binding peptides for the first time. Based on the PLABS screening platform, the researchers conducted a complete round of directed evolution and obtained the efficient mutant V2 (Cg-Def S19K/K10L/N13H). Compared with the wild type, the PLA binding specificity of V2 was increased by 2.3-fold. Contact angle and surface plasmon resonance measurements confirmed the specific binding of V2 to PLA (PLA surface coverage increased by 1.30 times). In summary, the PLABS screening platform established in this study represents a universal method for designing PLA-specific binding peptides for detection, sorting, and specific degradation of PLA in mixed plastics.

The researchers believe that the newly established PLABS screening platform will help design specific binding peptides for other materials and enable specific polymer tags and selective degradation of mixed plastic waste that are critical to the circular polymer economy.

In summary, some researchers have successfully developed a high-throughput screening system (PLABS) based on a 96-well microplate to improve the binding specificity of polylactic acid. PLABS was combined with KnowVolution, an efficient protein engineering strategy, to modify the polylactic acid-binding peptide Cg-Def. Verified by various detection methods such as contact angle and surface plasmon resonance, the polylactic acid binding specificity of the mutant has been significantly improved and is expected to be used in the sorting of mixed plastics.