New Proteins for new threads

**詹姆斯·默里博士提出了一种利用深度学习和机器学习引导技术的创新方法来生产布料，这有可能快速实现纺织业向可持续发展的过渡。**时尚产业是造成**严重环境问题的**前三大行业之一，占全球碳排放量的10%（超过英国、法国和德国碳足迹的总和）。其中大部分来自纺织材料生产，因为它严重依赖牲畜和石油基材料，这些材料在制造过程中与二氧化碳排放以及水和微塑料污染有关。据估计，如果不做出重大改变，到2050年，时尚行业将占全球碳足迹的26%。**该项目直接解决了纺织纤维可持续生产的需求。因此，Murray博士和合作者将开发一种新型蛋白质，这种蛋白质可以纺成纤维，并对纤维进行表征，从而为指导商业化努力提供见解。与动物来源的织物（有大量的碳足迹和使用大量的淡水）和合成石油基织物（不能生物降解）相比，这种新型生物材料将更具可持续性。这种新方法的独特之处有两个方面：首先，蛋白质将使用先进的深度学习方法从头设计；其次，机器学习将指导微生物菌株的开发，利用精密发酵（PF）（通过微生物繁殖来产生特定的产品）生产蛋白质。PF是唯一允许大规模生成新蛋白质的方法。这项技术是零残忍的，因为它不需要使用动物，而且它的碳足迹很低。Murray博士将运用他在蛋白质开发方面的专业知识来设计一种具有理想特性的新型蛋白质，这种蛋白质将用于制造耐用的纤维，适用于生产柔软透气的织物。通过与英国生物技术公司Eden Bio的合作，他将能够选择高产微生物菌株，以满足使用ML技术在时尚行业大规模生产的需求。总而言之，目前的项目提供了一种创新，能够显著提高英国最大行业之一的可持续性。

**Dr James Murray proposes an innovative approach to cloth production using deep learning and machine-learning-guided technology, which has the potential to fast-track the textile industry's transition to sustainability.**The fashion industry is among the **top 3 industries causing severe environmental problems**, contributing to 10% of carbon emissions globally (more than the total carbon footprint of the UK, France, and Germany combined). The majority comes from textile material production, as it relies heavily on livestock and petroleum-based materials, which are associated with CO2 emissions during manufacturing, as well as water and microplastic pollution. It's estimated that without drastic changes, the fashion industry will account for **26% of the global carbon footprint by 2050\.**This project addresses the need for sustainable production of textile fibres head-on. As such, Dr Murray and collaborators will develop a novel protein that can be spun into fibre and characterise the fibre to provide insights to guide commercialisation efforts. Compared to animal-derived fabrics (which have heavy carbon footprints and use a lot of fresh water) and synthetic petroleum-based fabrics (that don't biodegrade), this novel biomaterial will be more sustainable.Two aspects make this novel approach unique:* first, the proteins will be designed _de novo_ using advanced deep-learning methods* second, machine learning will guide microorganism strain development for protein production using precision fermentation (PF) (multiplying microbes to create specific products). PF is the only approach that allows the generation of novel proteins at scale. This technology is cruelty-free since it doesn't require the use of animals, and its carbon footprint is low.Dr Murray will apply his expertise in developing proteins to the design of a novel protein with desirable features, which will be used to create durable fibres suitable for producing soft, breathable fabrics. Through collaborating with UK-based biotech company Eden Bio, he will enable the selection of high-yielding microorganism strains to meet the demands of mass production in the fashion industry using ML technology.In summary, the present project offers an innovation capable of significantly enhancing the sustainability of one of the biggest industries in the UK.