Ngara Tanyaradzwa R, Zeng Peiji, Zhang Houjin
Department of Biotechnology, College of Life Science and Technology, MOE KEY Laboratory of Molecular Biophysics Huazhong University of Science and Technology Wuhan China.
Imeta. 2022 Aug 17;1(4):e45. doi: 10.1002/imt2.45. eCollection 2022 Dec.
Microbial biodegradation of persistent organic pollutants (POPs) is an attractive, ecofriendly, and cost-efficient clean-up technique for reclaiming POP-contaminated environments. In the last few decades, the number of publications documenting POP-degrading microbes, enzymes, and experimental data sets has continuously increased, necessitating the development of a dedicated web resource that catalogs consolidated information on POP-degrading microbes and tools to facilitate integrative analysis of POP degradation data sets. To address this knowledge gap, we developed the Microbial Biodegradation of Persistent Organic Pollutants Database (mibPOPdb) by accumulating microbial POP degradation information from the public domain and manually curating published scientific literature. Currently, in mibPOPdb, there are 9215 microbial strain entries, including 184 gene (sub)families, 100 enzymes, 48 biodegradation pathways, and 593 intermediate compounds identified in POP-biodegradation processes, and information on 32 toxic compounds listed under the Stockholm Convention environmental treaty. Besides the standard database functionalities, which include data searching, browsing, and retrieval of database entries, we provide a suite of bioinformatics services to facilitate comparative analysis of users' own data sets against mibPOPdb entries. Additionally, we built a Graph Neural Network-based prediction model for the biodegradability classification of chemicals. The predictive model exhibited a good biodegradability classification performance and high prediction accuracy. mibPOPdb is a free data-sharing platform designated to promote research in microbial-based biodegradation of POPs and fills a long-standing gap in environmental protection research. Database URL: http://mibpop.genome-mining.cn/.
持久性有机污染物(POPs)的微生物生物降解是一种具有吸引力、生态友好且成本效益高的清理技术,用于修复受POPs污染的环境。在过去几十年中,记录POPs降解微生物、酶和实验数据集的出版物数量不断增加,因此需要开发一个专门的网络资源,对有关POPs降解微生物的综合信息和工具进行编目,以促进对POPs降解数据集的综合分析。为了填补这一知识空白,我们通过从公共领域积累微生物POPs降解信息并人工整理已发表的科学文献,开发了持久性有机污染物微生物生物降解数据库(mibPOPdb)。目前,在mibPOPdb中,有9215个微生物菌株条目,包括184个基因(亚)家族、100种酶、48条生物降解途径以及在POPs生物降解过程中鉴定出的593种中间化合物,还有《斯德哥尔摩公约》环境条约下列出的32种有毒化合物的信息。除了标准的数据库功能,包括数据搜索、浏览和数据库条目的检索外,我们还提供了一套生物信息学服务,以促进用户自己的数据集与mibPOPdb条目的比较分析。此外,我们构建了一个基于图神经网络的化学物质生物降解性分类预测模型。该预测模型表现出良好的生物降解性分类性能和较高的预测准确性。mibPOPdb是一个免费的数据共享平台,旨在促进基于微生物的POPs生物降解研究,并填补环境保护研究中长期存在的空白。数据库网址:http://mibpop.genome-mining.cn/