AMITY Institute of Biotechnology, AMITY University Uttar Pradesh, Lucknow, UP, 227105, India.
Indian Institute of Toxicology Research, CSIR, Lucknow, UP, 226 001, India.
Microb Pathog. 2018 Jan;114:340-343. doi: 10.1016/j.micpath.2017.11.059. Epub 2017 Dec 2.
Chemical substances not showing any importance in existence of biological systems and causing serious health hazards may be designated as Xenobiotic compound. Elimination or degradation of these unwanted substances is a major issue of concern for current time research. Process of biodegradation is a very important aspect of current research as discussed in current manuscript. Current study focuses on the detailed mining of data for the construction of microbial consortia for wide range of xenobiotics compounds. Intensive literature search was done for the construction of this library. Desired data was retrieved from NCBI in fasta format. Data was analysed through homology approaches by using BLAST. This homology based searched enriched with a great vision that not only bacterial population but many other cheap and potential sources are available for different xenobiotic degradation. Though it was focused that bacterial population covers a major part of biodegradation which is near about 90.6% but algae and fungi are also showing promising future in degradation of some important xenobiotic compounds. Analysis of data reveals that Pseudomonas putida has potential for degrading maximum compounds. Establishment of correlation through cluster analysis signifies that Pseudomonas putida, Aspergillus niger and Skeletonema costatum can have combined traits that can be used in finding out actual evolutionary relationship between these species. These findings may also givea new outcome in terms of much cheaper and eco-friendly source in the area of biodegradation of specified xenobiotic compounds.
化学物质在生物系统中没有表现出任何重要性,却会导致严重的健康危害,这些物质可能被指定为异源化合物。消除或降解这些不需要的物质是当前研究关注的主要问题。正如本文所述,生物降解过程是当前研究的一个非常重要的方面。本研究专注于详细挖掘数据,以构建用于多种异源化合物的微生物群落。为此进行了深入的文献检索来构建这个文库。从 NCBI 以 FASTA 格式检索所需的数据。通过 BLAST 进行同源性分析来对数据进行分析。这种基于同源性的搜索提供了一个广阔的视野,不仅细菌种群,还有许多其他廉价且有潜力的来源可用于不同异源化合物的降解。虽然重点是细菌种群几乎占生物降解的 90.6%,但藻类和真菌在降解一些重要异源化合物方面也显示出了有前途的未来。数据分析表明,假单胞菌(Pseudomonas putida)具有降解最多化合物的潜力。通过聚类分析建立相关性表明,假单胞菌(Pseudomonas putida)、黑曲霉(Aspergillus niger)和骨条藻(Skeletonema costatum)可以具有组合特征,可用于发现这些物种之间的实际进化关系。这些发现也可能在指定异源化合物生物降解方面提供更廉价和环保的来源的新结果。