Lin Xiaoxing, Zhang Rui, Cui Feng-Qi, Hong Wenqing, Yang Shu, Ju Feng, Xi Chuanwu, Sun Xiao, Song Liyan
School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China.
Institute of Advanced Technology, University of Science and Technology of China, Hefei 230601, China.
PNAS Nexus. 2025 Mar 18;4(3):pgaf066. doi: 10.1093/pnasnexus/pgaf066. eCollection 2025 Mar.
Biodegradation is a promising and environmentally friendly strategy for plastic pollution management. Landfills decompose municipal solid waste, including almost 50% of global plastic debris and even some of the oldest synthetic plastics, fostering naturally selected plastic biodegradation. Herein, we present a global collection of plastic biocatalytic enzymes from landfills using metagenomics and machine learning. Metagenomic analysis identified 117 plastic-degrading genes, with 39 incorporated in 22 prokaryotic metagenome-assembled genomes (MAGs). A machine-learning approach predicted 978,107 candidate plastic-degrading genes, 712 of which were encoded respectively by 150 MAGs. Our results highlight landfills as reservoirs of diverse, naturally selected plastic-degrading microbes and enzymes, serving as references and/or models for biocatalysis engineering and in situ bioremediation of plastic pollution.
生物降解是一种很有前景且环保的塑料污染治理策略。垃圾填埋场会分解城市固体废弃物,其中包括全球近50%的塑料碎片,甚至还有一些最古老的合成塑料,这促进了自然选择的塑料生物降解。在此,我们利用宏基因组学和机器学习展示了一个来自垃圾填埋场的塑料生物催化酶的全球集合。宏基因组分析鉴定出117个塑料降解基因,其中39个整合在22个原核宏基因组组装基因组(MAG)中。一种机器学习方法预测出978,107个候选塑料降解基因,其中712个分别由150个MAG编码。我们的结果突出了垃圾填埋场作为多样的、自然选择的塑料降解微生物和酶的储存库,可为生物催化工程和塑料污染的原位生物修复提供参考和/或模型。