© 2024 SURF
Plastic waste is one of the largest environmental problems in the 21st century. By 2050, up to 12,000 Mt of plastic waste is estimated to be in landfills or in the natural environment. Biochemical recycling by using modified microbial enzymes have shown potentials in the back-to-monomer (BTM) recycling of polyethylene terephthalate by breaking down the polymers into re-usable monomers. These enzymes can be produced via fungal species. In order to make this biochemical BTM process viable a process integrated enzyme production is key in increasing the efficiency and reducing the cost of enzymes. For this a molecular monitoring method, such as RNA-seq (RNA-sequencing), is needed. RNA-seq can achieve a snapshot on enzyme producing process inside of the cell by semi-quantitatively measuring the volume of enzyme encoding RNAs. This information can bring hints on fungal strain improvement by promoting the desired enzymes. It also helps to instantly monitor the BTM production outcomes. However, conventional RNA-seq platforms can only be performed via service providers or startup investments reaching 2 million euros. Each round of analysis could take as long as 6 weeks turnaround time. Furthermore, the method creates huge amount of complicated datasets, only by expert skills and specialized high performance computing the data can be sorted in a comprehensive manner. To solve these problems, in this project, by combining the expertise on plastic end-of-life control, fungal enzyme production, molecular monitoring and Bioinformatics from both the UAS and SME sides, we aim to implement a novel RNA-seq based system to monitor the in-process enzyme production for plastic degradation. We will optimize the existing portable RNA-seq prototype machinery for semi-real time monitoring of the BTM recycling process. The downstream data will be handled by a tailored analysis pipeline designed with expert knowledge via an user-friendly interface.