Assessing the genetic diversity of Cu resistance in mine tailings through high-throughput recovery of full-length copA genes.
AuthorLi, X; Zhu, Y-G; Shaban, B; Bruxner, TJC; Bond, PL; Huang, L
Source TitleScientific Reports
PublisherSpringer Science and Business Media LLC
University of Melbourne Author/sShaban, Babak
Document TypeJournal Article
CitationsLi, X., Zhu, Y. -G., Shaban, B., Bruxner, T. J. C., Bond, P. L. & Huang, L. (2015). Assessing the genetic diversity of Cu resistance in mine tailings through high-throughput recovery of full-length copA genes.. Sci Rep, 5 (1), pp.13258-. https://doi.org/10.1038/srep13258.
Access StatusOpen Access
Open Access at PMChttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4541151
Characterizing the genetic diversity of microbial copper (Cu) resistance at the community level remains challenging, mainly due to the polymorphism of the core functional gene copA. In this study, a local BLASTN method using a copA database built in this study was developed to recover full-length putative copA sequences from an assembled tailings metagenome; these sequences were then screened for potentially functioning CopA using conserved metal-binding motifs, inferred by evolutionary trace analysis of CopA sequences from known Cu resistant microorganisms. In total, 99 putative copA sequences were recovered from the tailings metagenome, out of which 70 were found with high potential to be functioning in Cu resistance. Phylogenetic analysis of selected copA sequences detected in the tailings metagenome showed that topology of the copA phylogeny is largely congruent with that of the 16S-based phylogeny of the tailings microbial community obtained in our previous study, indicating that the development of copA diversity in the tailings might be mainly through vertical descent with few lateral gene transfer events. The method established here can be used to explore copA (and potentially other metal resistance genes) diversity in any metagenome and has the potential to exhaust the full-length gene sequences for downstream analyses.
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