| Literature DB >> 26887227 |
Arif Tasleem Jan1, Mudsser Azam2, Inho Choi3, Arif Ali2, Qazi Mohd Rizwanul Haq2.
Abstract
Mercury, which is ubiquitous and recalcitrant to biodegradation processes, threatens human health by escaping to the environment via various natural and anthropogenic activities. Non-biodegradability of mercury pollutants has necessitated the development and implementation of economic alternatives with promising potential to remove metals from the environment. Enhancement of microbial based remediation strategies through genetic engineering approaches provides one such alternative with a promising future. In this study, bacterial isolates inhabiting polluted sites were screened for tolerance to varying concentrations of mercuric chloride. Following identification, several Pseudomonas and Klebsiella species were found to exhibit the highest tolerance to both organic and inorganic mercury. Screened bacterial isolates were examined for their genetic make-up in terms of the presence of genes (merP and merT) involved in the transport of mercury across the membrane either alone or in combination to deal with the toxic mercury. Gene sequence analysis revealed that the merP gene showed 86-99% homology, while the merT gene showed >98% homology with previously reported sequences. By exploring the genes involved in imparting metal resistance to bacteria, this study will serve to highlight the credentials that are particularly advantageous for their practical application to remediation of mercury from the environment.Entities:
Keywords: Bioremediation; Mercury; Mercury transport; Resistance determinants
Mesh:
Substances:
Year: 2016 PMID: 26887227 PMCID: PMC4827696 DOI: 10.1016/j.bjm.2015.11.023
Source DB: PubMed Journal: Braz J Microbiol ISSN: 1517-8382 Impact factor: 2.476
Growth of bacterial isolates in presence of varying concentrations of mercuric chloride.
| Conc | ARY1 ( | ARY4 ( | ARY2 ( | ARY7 ( | ARY3 ( | ARTK3 ( | ARH4 ( | ARFA ( | ARFB ( | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.1 μM | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ |
| 1 μM | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ |
| 10 μM | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ | ++ |
| 100 μM | + | ++ | ++ | + | ++ | + | ++ | + | ++ | ++ |
| 1000 μM | – | ++ | ++ | – | ++ | – | ++ | – | – | – |
| 10,000 μM | – | – | – | – | – | – | – | – | – | – |
++, good growth; +, less (late) growth; –, no growth.
Phylogenetic affiliation and GenBank accession numbers of merP and merT gene sequences of bacterial isolates investigated in this study.
| Sample collection site | Best match (GenBank Acc. no.) | Similarity (%) | Microbial group affiliation | GenBank Acc. no. of 16S rRNA | GenBank Acc. no. of | GenBank Acc. no. of |
|---|---|---|---|---|---|---|
| Rajkot drain (Gujrat), India | 99.7 | |||||
| Hoogly river (Kolkata), India | 99.8 | |||||
| Hoogly river (Kolkata), India | Uncultured bacteria ( | 98.8 | – | |||
| Yamuna river (Agra), India | 99.4 | |||||
| Kodaikanal lake (Tamilnadu), India | 99.3 | – | – | |||
| Kodaikanal lake (Tamilnadu), India | 98.9 | |||||
| Kodaikanal lake (Tamilnadu), India | 99.7 | – | ||||
| Hindon river (Ghaziabad), India | Uncultured γ-proteobacteria ( | 98.9 | ||||
| Hindon river (Ghaziabad), India | 98.6 | |||||
| Yamuna river (Okhla), India | 99.8 | |||||
| Yamuna river (Okhla), India | Uncultured bacteria ( | 99.4 | JNN188342 | |||
| Yamuna river (Agra), India | Uncultured bacteria ( | 99.2 | ||||
| Yamuna river (Faridabad), India | 99.5 | – | – | |||
| Najafgarh drain (Delhi), India | 99.4 | – | ||||
| Najafgarh drain (Delhi), India | 99.5 | – | – | |||
| Najafgarh drain (Delhi), India | 99.2 | |||||
| Najafgarh drain (Delhi), India | 99.7 | – | – | |||
| Najafgarh drain (Delhi), India | 99.6 | – | ||||
| Najafgarh drain (Delhi), India | 99.4 | – | – |
Fig. 1Phylogram drawn using the neighbor net method (bootstrap analysis with 1000 replicates) illustrating phylogenetic relationships based on multiple alignments of merP nucleotide sequences from studied isolates with other known sequences.
Fig. 2Phylogram drawn using the neighbor net method (bootstrap analysis with 1000 replicates) illustrating phylogenetic relationship based on multiple alignments of merT nucleotide sequences from studied isolates with other known sequences.
Fig. 3Phylogram drawn using the neighbor net method (bootstrap analysis with 1000 replicates) illustrating phylogenetic relationships based on multiple alignments of MerP sequences from studied isolates with other known sequences.
Fig. 4Phylogram drawn using the neighbor net method (bootstrap analysis with 1000 replicates) illustrating phylogenetic relationships based on multiple alignments of MerT sequences from studied isolates with other known sequences.