1. Background
Biological diversity, commonly known as biodiversity, is variety of life on the Earth. Biodiversity is recognized as the main factor affecting ecosystem performance. Microbial diversity is related to material cycling, biogeochemical processes, ecosystem stability and productivity. Ecosystem biodiversity is critical for its sustainability and better exploitation of ecosystem potentials ( 1 ). Therefore, it is necessary to realize how microbial diversity is related to the community structure and its function ( 2 - 4 ). Microorganisms that live in the soil are of particular importance because represent the largest pool of biodiversity on Earth ( 4 , 5 ). Bacteria are the source of many different biological processes and metabolites that can significantly affect the ecosystem. Variety in these processes and products confirm bacterial genetic diversity. Therefore, the systematic study of bacteria can make significant progress in understanding of the metabolic processes which can be used to improve environmental and living conditions ( 6 ). In this regard, metal mines, due to their extreme environmental conditions, are generally considered as attractive resources for microbial diversity studies. Mine indigenous microorganisms, which are alive under these conditions, may have suitable applications in biotechnology and biological processes such as bioremediation. Since the Forumad area is an extreme environment with high concentrations of chromite and magnesite and alkaline pH; it seems the microbial population of this ecosystem can tolerate heavy metals, and may be a suitable source for identifying microorganisms that can be used for environmental applications.
In diversity analysis, since many environmental microorganisms are non-cultivable, metagenomics-based approaches, as a combination of genomic and bioinformatics technologies, are developed for detailed elaboration on the genetic diversity of microbial community of soil, sediments and aquatic environments ( 7 ) which used to assess cultivable and non-cultivable microorganisms ( 8 , 9 ). The 16S rRNA gene is a relatively short conserved DNA segment to identify bacteria and thus, serves as a more time and cost-effective strategy, as compared to many other unique bacterial genes, to predict phylogenetic relationships ( 10 , 11 ). According to this, the strains with about 98.5% ribosomal RNA gene similarity or less are unlikely to have more than 60 to 70% genomic DNA similarity and therefore, are categorized as different species. However, the opposite is not always true, and if the 16S rRNA gene sequences similarity is higher than 98.5%, yet they may be introduced as different or the same species ( 12 , 13 )
2. Objectives
In this study, microbial diversity of an ore mine in Iran, the Forumad chromite area, was evaluated using a metagenomics-based approach and the evolutionary relationship of the identified strains was compared with those recorded in biological databases. Since the 16S rRNA gene-based assay provides a rapid and broad-spectrum analysis platform to reliably identify the microbial diversity, we used this approach for identification of the unexplored microbial diversity in this mine located at Sabzevar ophiolitic belt, Northeastern Iran.
3. Materials and Methods
3.1. Site Description and Sample Collection
The Forumad chromite deposit is located within the Sabzevar ophiolitic complex (SOC) at 1,500 meters above the sea level with a long time mining activities. The mean concentrations of Cr (5837.5 ppm) and Ni (570.7 ppm) in the nearby environment are significantly high. The mean concentrations of other heavy metals existing in the region such as As, Cd, Co, Cu, Pb, and V are also close to the geological background values ( 14 ).
The samples were collected from eight different sites of the Forumad chromite area (effluent water, mine’s soil and soil around mines) at spring and autumn of 2011. Classical sampling methods were performed in sterile bottles and the samples were transported to the laboratory on ice as soon as possible.
3.2. DNA Extraction
In diversity studies based on metagenomics approaches, preparation of enough high quality DNA, especially from soil and other samples containing humic acid or other contaminants, is critical. Therefore, in this study, several DNA extraction kits and manual methods were used. The highest amount of DNA was gained through a combination of Zhou’s manual method ( 15 ) and MOBIO Kit. High amounts of crude DNA were extracted from 5 g of each sample by Zhou’s method and purified by MOBIO Kit according to the manufacturer`s instruction
3.3. 16S rRNA Gene Amplification and Library Cons-truction
Pure metagenoms were PCR amplified for bacterial and archaeal 16S rRNA genes using the universal primers (Table 1, Supplementary data). One hundred Nano gram of DNA was used in a PCR reaction mixture (final volume of 50 µL) containing 1.5 mM MgCl2, 1X Reaction buffer, 0.2 mM dNTP, 5 pmoL of each primer and 2.5 U Taq DNA polymerase. PCR was performed with an initial denaturation at 95 °C for 5 min, followed by 30 cycles of 95 °C for 60 s (denaturation), 50-54 °C for 60 s (annealing), 72 °C for 1.5 min (extension) and 72 °C for 10 min (final extension). The PCR products were visualized on 1% agarose gel in TAE buffer and then purified using the Roche High pure PCR purification kit.
The amplicons were ligated into pTz57 R/T vector, according to the Fermentas’s protocol. Ligation products were transformed into E. coli DH5α cells by heat shock transformation method ( 16 ) and screened on LB/Ampicillin/IPTG/X-Gal plates in 37 °C for 16 h. The positive clones were selected based on the blue-white screening method; accordingly, white colonies were considered as recombinant clones and confirmed by PCR using vector specific primers M13F (5ˊ-GTAAAACGACGGCCAG-3ˊ) and M13R (5ˊ- CAGGAAACAGCTATGAC-3ˊ) ( 17 ). Then, plasmids were extracted from positive clones by plasmid extraction Kit (Roche, Germany) for sequencing (Sanger method, Macrogen, South Korea).
3.4. Phylogenetic Analysis
The sequences were edited using Chromas Pro program (Technelysium Pty Ltd, Australia) and checked by Bellerphon program ( 18 ) for chimers in amplified fragments. BLAST program in NCBI and EzTaxon databases ( 19 ) were used to identify and compare similar 16S rDNA sequences. Phylogenetic analysis was performed using the MEGA5 software ( 20 ) after multiple alignments of sequences available from EzTaxon database by CLUSTAL X ( 21 ). Pairwise evolutionary distances were computed using the correction method and clustering was performed using the neighbor-joining method ( 22 ). Bootstrap analysis was used to evaluate the tree topology by means of 100 alternative trees.
4. Results
4.1. Physicochemical Parameters of the Samples
The geographical location of the sampling sites is presented in Table 2 in Supplementary data. The samples pH was around 9. The type and amount of ionic compounds available in the Forumad chromite mine are shown in Table 3 in Supplementary data. The maximum amount of compounds belongs to the chromite oxide (41%) which indicates the presence of large amounts of chromium in this area.
4.2. 16S rDNA Library
Two 16S rRNA gene libraries from soil samples (Bacterial-Archaeal) and one library from water samples (Bacterial) were constructed in E. coli DH5α. No archaea PCR products was obtained from the water samples. Total of 248 white colonies were maintained at the libraries of the soil and water samples, from which 56 bacterial colons of the water samples (Prefix FMW-Bac), 32 bacterial colons of the soil samples (Prefix FMS-Bac) and 19 archaeal colons of the soil samples (Prefix FMS-Arc) were randomly sequenced. Four identical sequences and also 17 bacterial incomplete sequences of the water samples were excluded from the study. The 83 sequences (39 Bacteria from water samples, 29 Bacteria from soil samples and 15 Archaea from soil samples) were deposited in GenBank wit h accession numbers KF975505-KF975587 (Tables 1, 2 and 3). Accordingly, frequency of the Gammaproteobacterial strains in water libraries and Alphaproteobacterial and Gammaproteobacterial strains in soil libraries were dominant, respectively.
Clone Library | Accession No. | Sequene length bp | Closest sequence match in NCBI | Similarity % | Closest sequence match in EzTaxon | Similarity % |
---|---|---|---|---|---|---|
Bacteria of water samples | ||||||
FMWB1 | KF975505 | 1496 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 99.56 |
FMWB2 | KF975506 | 1496 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 99.48 |
FMWB6 | KF975510 | 1533 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 99.21 |
FMWB9 | KF975513 | 1496 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 99.12 |
FMWB10 | KF975514 | 1359 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 99.11 |
FMWB17 | KF975521 | 1497 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 98.89 |
FMWB18 | KF975522 | 1496 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 98.82 |
FMWB21 | KF975525 | 1500 | Enterobacter sp. Bn-12 JX456175.1 | 99 | Cedeceaneteri GTC1717(T) AB086230 | 98.75 |
FMWB3 | KF975507 | 1525 | elftia acidovoransSPH1strain SPH-1 NR074691.1 | 99 | Delftia lacustrisDSM 21246 (T) EU888308 | 99.33 |
FMWB4 | KF975508 | 1448 | Acidovorax sp. Asd MW-A3 FM955883.1 | 99 | Acidovorax radicisN35(T) AFBG0100003 | 99.31 |
FMWB5 | KF975509 | 1530 | Pseudomonas anguilliseptica strain BI AF439803.1 | 99 | Pseudomonas peli R-20805(T)AM114534 | 99.25 |
FMWB7 | KF975511 | 1514 | Rheinheimera soli strain BD-d46NR044294.1 | 99 | Rheinheimera soli BD-d46(T)EF575565 | 99.19 |
FMWB8 | KF975512 | 1517 | Rheinheimera solistrain BD-d46NR044294.1 | 99 | heinheimera soli BD-d46(T)EF575565 | 99.19 |
FMWB16 | KF975520 | 1489 | Rheinheimera solistrain BD-d46NR044294.1 | 99 | Rheinheimera soli BD-d46(T)EF575565 | 98.92 |
FMWB19 | KF975523 | 1517 | Rheinheimera solistrain BD-d46NR044294.1 | 99 | Rheinheimera soli BD-d46(T)EF575565 | 98.79 |
FMWB24 | KF975528 | 1518 | Rheinheimera sp. BZ19 GQ240227.1 | 99 | Rheinheimera soli BD-d46(T)EF575565 | 98.58 |
FMWB31 | KF975535 | 1517 | Rheinheimera sp. BZ19 GQ240227.1 | 98 | Rheinheimera soli BD-d46(T)EF575565 | 98.52 |
FMWB33 | KF975537 | 1518 | Rheinheimera sp. BZ19 GQ240227.1 | 97 | Rheinheimera chironomiK19414(T) DQ298025 | 97.97 |
FMWB12 | KF975516 | 1487 | Limnobacter thiooxidans strain HLSB157 FJ999570.1 | 99 | Limnobacter thiooxidans CS-K2(T) AJ289885 | 99.10 |
FMWB14 | KF975518 | 1487 | Limnobacter sp. e8(2011) HQ652592.1 | 99 | Limnobacter thiooxidans CS-K2(T) AJ289885 | 99.03 |
FMWB22 | KF975526 | 1486 | Limnobacter sp. e8(2011) HQ652592.1 | 99 | Limnobacter thiooxidans CS-K2(T) AJ289885 | 98.62 |
FMWB23 | KF975527 | 1526 | Hydrogenophaga sp. CL3 DQ986320.1 | 99 | Hydrogenophaga taeniospiralisATCC 49743 (T) AF078768 | 98.59 |
FMWB27 | KF975531 | 1462 | Runella sp. NBRC 15128 AB680774.1 | 99 | Runella slithyformis DSM 19594(T) CP002859 | 98.04 |
FMWB11 | KF975515 | 1529 | Uncultured JQ824901.1 | 99 | Uncultured EF540413 | 99.11 |
FMWB13 | KF975517 | 1494 | Uncultured AF523040.1 | 99 | Polaromonas jejuensisJS12-13(T) EU030285 | 99.08 |
FMWB15 | KF975519 | 1501 | Uncultured JN392908.1 | 99 | Pseudomonas peliR20805(T) AM114534 | 98.92 |
FMWB20 | KF975524 | 1445 | Uncultured KC683142.1 | 99 | Bradyrhizobium lablabiCCBAU23086(T) GU433448 | 98.75 |
FMWB25 | KF975529 | 1521 | Uncultured JN685475.1 | 99 | Aquabacterium parvum B6(T) AF035052 | 98.51 |
FMWB26 | KF975530 | 1497 | Uncultured AB583905.1 | 99 | Hydrogenophaga taeniospiralis ATCC 49743 (T) AF078768 | 98.32 |
FMWB28 | KF975532 | 1488 | Uncultured AF445684.1 | 99 | Algoriphagus boritolerans T-22(T) AB197852 | 97.82 |
FMWB29 | KF975533 | 1527 | Uncultured EF632936.1 | 99 | Curvibacter delicates LMG 4328 (T) AF078756 | 97.44 |
FMWB30 | KF975534 | 1478 | Uncultured FJ801195.1 | 99 | Flavobacterium chungangense CJ(T)EU924275 | 97.18 |
FMWB32 | KF975536 | 1519 | Uncultured JN869095.1 | 98 | Rheinheimera chironomiK19414(T) DQ298025 | 98.44 |
FMWB34 | KF975538 | 1544 | Uncultured JN178248.1 | 97 | Anaerobacillus macyae JMM-4 (T) AY032601 | 97.19 |
FMWB35 | - | 1529 | Uncultured JN392908.1 | 96 | Pseudomonas peliR20805(T) AM114534 | 95.39 |
FMWB36 | KF975539 | 1549 | Uncultured Opitutales AB479055.1 | 94 | Uncultured AB479055 | 94.13 |
FMWB37 | KF975540 | 1489 | Uncultured JN488684.1 | 93 | Uncultured DQ329894 | 88.68 |
FMWB38 | KF975541 | 1502 | Uncultured Sphingobacteria EF520608.1 | 91 | Uncultured EU753655 | 87.50 |
FMWB39 | KF975542 | 1507 | Uncultured Sphingobacteria EF520608.1 | 91 | Uncultured AB369173 | 87.36 |
FMWB40 | KF975543 | 1507 | Uncultured Sphingobacteria EF520608.1 | 89 | Uncultured EU328009 | 85.02 |
Clone Library | Accession No. | Sequene length bp | Closest sequence match with NCBI | Similarity % | Closest sequence match with EzTaxon | Similarity % |
---|---|---|---|---|---|---|
Bacteria of Soil samples | ||||||
FMSB1 | KF975544 | 1530 | Ralstonia pickettii12J strain 12J NR102967.1 | 99 | Ralstonia pickettii ATCC 27511 (T) AY741342 | 99.8 |
FMSB9 | KF975552 | 1497 | Ralstonia sp. NT80 AB740040.1 | 98 | Ralstonia insidiosa AU2944(T) AF488779 | 98.39 |
FMSB2 | KF975545 | 1529 | Pseudomonas sp. MBR EU307111.2 | 99 | Pseudomonas toyotomiensisHT-3(T) AB453701 | 99.8 |
FMSB3 | KF975546 | 1529 | Pseudomonas sp. MBR EU307111.2 | 99 | Pseudomonas toyotomiensisHT-3(T) AB453701 | 99.7 |
FMSB4 | KF975547 | 1528 | Pseudomonas sp. MBR EU307111.2 | 99 | Pseudomonas toyotomiensisHT-3(T) AB453701 | 99.46 |
FMSB5 | KF975548 | 1516 | Arthrobacter sp. EM5 FJ517625.1 | 99 | Arthrobacter scleromaeYH-2001 AF330692 | 98.87 |
FMSB13 | KF975556 | 1478 | Pseudanabaena sp. Sai011 GU935357.1 | 98 | Oscillatoria limnetica MR1 AJ007908 | 97.72 |
FMSB6 | KF975549 | 1495 | Uncultured KF511881.1 | 99 | Silanimonas lenta25-4(T) AY557615 | 97.47 |
FMSB7 | KF975550 | 1537 | Uncultured HQ119931.1 | 99 | Pseudoxanthomonas sacheonensisBD-c54(T) EF575564 | 97.41 |
FMSB11 | KF975554 | 1500 | Uncultured AF467297.1 | 98 | Pseudoxanthomonas yeongjuensis GR12-1(T) DQ438977 | 98.07 |
FMSB8 | KF975551 | 1519 | Uncultured Acidobacteria FR749746.1 | 98 | Uncultured FR749746 | 98.52 |
FMSB14 | KF975557 | 1548 | Uncultured Acidobacteria HQ597972.1 | 98 | uncultured HM438150 | 97.69 |
FMSB10 | KF975553 | 1440 | Uncultured AY957902.1 | 98 | Erythromicrobium ramosumDSM 8510 (T) AF465837 | 98.37 |
FMSB12 | KF975555 | 1530 | Uncultured JQ769882.1 | 98 | uncultured DQ378223 | 97.86 |
FMSB15 | KF975558 | 1516 | Uncultured AF445684.1 | 98 | Algoriphagus boritoleransT-22(T) AB197852 | 97.34 |
FMSB16 | KF975559 | 1445 | Uncultured KC683122.1 | 98 | Bosea minatitlanensis AMX51(T), AF273081 | 93.75 |
FMSB17 | KF975560 | 1443 | Uncultured KC683122.1 | 98 | Bosea massiliensis63287(T) AF288309 | 93.70 |
FMSB21 | KF975564 | 1445 | Uncultured KC683122.1 | 97 | Bosea massiliensis63287(T) AF288309 | 93.56 |
FMSB22 | KF975565 | 1445 | Uncultured KC683122.1 | 97 | Bosea minatitlanensis AMX51(T), AF273081 | 93.46 |
FMSB23 | KF975566 | 1506 | Uncultured FJ592715.1 | 97 | Uncultured HQ327283 | 91.30 |
FMSB24 | KF975567 | 1506 | Uncultured JQ711705.1 | 97 | Uncultured GQ116319 | 91 |
FMSB25 | KF975568 | 1441 | Uncultured AB757744.1 | 97 | Thermosynechococcus elongatusBP-1 BA000039 | 90.19 |
FMSB26 | KF975569 | 1532 | Uncultured JN178820.1 | 97 | Gemmatimonas aurantiacaT-27(T) AP009153 | 83.20 |
FMSB27 | - | 1421 | Uncultured Rhodobacteraceae FJ516816.1 | 96 | Rubrimonas shengliensis SL014B-28A2(T) GU125651 | 92.81 |
FMSB18 | KF975561 | 1549 | Uncultured KC011114.1 | 97 | Uncultured GQ472363 | 97.42 |
FMSB28 | KF975570 | 1548 | Uncultured JQ978959.1 | 94 | Uncultured GQ472363 | 94.5 |
FMSB29 | - | 1489 | Uncultured JX225716.1 | 93 | Uncultured AY79604 | 91.25 |
FMSB30 | KF975571 | 1478 | Uncultured Planctomycetales JN825575.1 | 92 | Phycisphaer amikurensisNBRC 102666 (T), AP012338 | 81.40 |
FMSB19 | KF975562 | 1515 | Uncultured JF449956.1 | 97 | Blastocatella fastidiosa A2-16(T) JQ309130 | 95.56 |
FMSB20 | KF975563 | 1515 | Uncultured Hymenobacter JN367223.1 | 97 | Adhaeribacter aquaticusMBRG1.5(T) AJ626894 | 95 |
FMSB31 | KF975572 | 1529 | Uncultured HQ397151.1 | 89 | Sphaerobacter thermophilus DSM 20745 (T), CP001824 | 79.41 |
Clone Library | Accession No. | Sequene length bp | Closest sequence match with NCBI | Similarity % | Closest sequence match with EzTaxon | Similarity % |
---|---|---|---|---|---|---|
Archaea of Soil samples | ||||||
FMSA1 | KF975573 | 1442 | Uncultured FJ784315.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 97.84 |
FMSA2 | KF975574 | 1442 | Uncultured FJ784315.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 97.49 |
FMSA3 | KF975575 | 1442 | Uncultured FJ784315.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 97.28 |
FMSA4 | KF975576 | 1441 | Uncultured FJ790536.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 95.5 |
FMSA5 | KF975577 | 1441 | Uncultured FJ790536.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 95.3 |
FMSA6 | KF975578 | 1441 | Uncultured EF690622.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 94.4 |
FMSA7 | KF975579 | 1441 | Uncultured EF690622.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 94.3 |
FMSA8 | KF975580 | 1441 | Uncultured EF690622.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 94.27 |
FMSA9 | KF975581 | 1441 | Uncultured EF690622.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 94 |
FMSA10 | KF975582 | 1441 | Uncultured FJ784309.1 | 99 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 93.85 |
FMSA11 | KF975583 | 1441 | Uncultured EF690622.1 | 98 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 95.67 |
FMSA12 | KF975584 | 1441 | Uncultured U62812.1 | 98 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 95.67 |
FMSA13 | KF975585 | 1441 | Uncultured EF690622.1 | 98 | Nitrososphaeragargensisenrichment culture Ga9.2 GU797786 | 95 |
FMSA14 | KF975586 | 1441 | Uncultured EF690622.1 | 98 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 94.83 |
FMSA15 | KF975587 | 1442 | Candidatus Nitrososphaera gargensis Ga9.2 NR102916.1 | 97 | Nitrososphaera gargensis enrichment culture Ga9.2 GU797786 | 97.28 |
4.3. Phylogenetic Analysis of Bacteria in the Water Samples
The 16S rRNA gene sequences of the bacterial library from the water samples were classified in 40 Operational Taxonomic Units (OTUs) falling into five phylogenetic phyla: Proteobacteria (30 OTUs - 75% of total bacterial colonies), Bacteroidetes (6 OTUs - 15%), Firmicutes (1 OTU - 2.5%), Verrucomicrobia (1 OTU - 2.5%) and uncultured (2 OTUs - 5%). The Proteobacteria group contains the largest section of the OTUs, the majority of which showed more similarity with Cedecea and Rheinheimera species (Fig. 1).
Figure 1. Phylogenetic tree of bacterial OTUs (soil samples) to show the phylogenetic relationships by Neibour-Joining algorithm and bootstrap analysis 100.
4.4. Phylogenetic Analysis of Bacteria in the Soil Samples
The 16S rRNA gene sequences of the bacterial library from the soil samples were classified in 31 OTUs, falling into nine phylogenetic phyla: Proteobacteria (14 OTUs - 45% of total colonies), Cyanobacterria (2 OTUs - 6.45%), Gemmatimonadetes (1 OTUs - 3.22%), Bacteroidetes (2 OTUs - 6.45%), Actinobacteria (1 OTUs - 3.22%), Acidobacteria (1 OTUs - 3.22%), Firmicutes (1 OTUs - 3.22%), Chloroflexi (1 OTUs - 3.22%), Planctomycetes (1 OTUs - 3.22%) and uncultured (7 OTUs - 22.5%). The Proteobacteria constitute the largest group of this library. Phylogenetic tree was constructed with the above mentioned and related strains from the Eztaxon database (Fig. 2).
Figure 2. Phylogenetic tree of bacterial OTUs (water samples) to show the phylogenetic relationships by Neibour-Joining algorithm and bootstrap analysis 100.
According to our results, although bacterial abundance of the soil library was less than that of the water library, the soil library was more diverse. On the other hand, 83% of its OTUs had less than 98.7% similarity to the recorded strains, meaning that they may represent new species.
4.5. Phylogenetic Analysis of Archaea in the Soil Samples
Strains of the archaea library were classified in Nitrososphaera, belonging to the Thaumarchaeota phylum with 15 OTUs. Comparison of the sequences together and with the closest recognized strains in terms of similarity (Fig. 3) shows that 68.6% of the sequences had less than 98.7% similarity with the recorded strains. These clones are often different, known as uncultured archaea, and probably represent new species.
Figure 3. Phylogenetic tree of archaeal OTUs (soil samples) to show the phylogenetic relationships by Neibour-Joining algorithm and bootstrap analysis 100.
5. Discussion
Generally, heavy metals, being toxic in nature, have detrimental effects on activities and performance of microorganisms. Such effects inhibit microbial nutrients recycling processes such as nitrogen mineralization in soil and thus, the soil respiration rate and microbial biomass are decreased ( 23 ). In study of microbiome of the heavy metal (chromite) mine, our analysis led to the identification of 86 independed OTUs in 107 clones of a 16S rRNA gene library consisting of 248 clones (less than 50% of the library) with only 4 identical sequences. Accordingly, it can be concluded that the Forumad area has limited microbial community (as biomass) with high diversity, which confirms the previous studies affirming the significant negative impact of heavy metals on microbial community ( 24 - 26 ). Low identical OTUs could be due to the fact that most microorganisms are unable to cope with harsh conditions such as low nutrients, drought, high sunlight ( 25 ), and/or the existence of toxic heavy metals for multiplication. Some microbial communities may tolerate high concentrations of heavy metals which could be attributed to the precipitation, adsorption, or biotransformation of heavy metals ( 23 , 27 ) or other resistance mechanisms. For instance, non-specific interactions with proteins or secondary metabolites, being capable of donating electrons to Cr (VI) and converting it into Cr (III), which may resulted in tolerance to chromium ( 25 ). Therefore, identification of these microbial communities with heavy metals bio-detoxification and bioremediation properties is an ecologically attractive finding with probable application in cleanup of the pollutants.
Accordingly, many studies have been conducted on bacterial diversity in the environments containing chromium that shown the Proteobacteria as dominant population ( 25 , 28 ). As expressed in these studies, tolerance to arsenic and chromium is widespread in Proteobacteria. Moreover, Alphaproteobacteria and Gammaproteo-bacteria were abundant in all these areas ( 25 ).
Also, another similar study on gold mine have confirmed that Proteobacteria constitute the biggest part of the clone libraries ( 29 ). Dhal et al. have compared two uranium-contaminated and non-uranium-contaminated regions. Proteobacteria were found in both areas; however, these bacteria were dominant in the uranium contaminated region ( 30 ). In addition, in a study of bacterial, fungal, and archaeal communities in a uranium mine, located in Eastern Finland, a total of 814 bacterial, 54 archaeal and 167 fungal genera were identified, in which Proteobacteria, Euryarchaeota, and Mortiriella were dominant bacterial, archaeal and fungal phyla, respectively ( 31 ). In the present study, the frequency of the Proteobacteria strains in both bacterial libraries related to water (the dominance of Gammaproteobacteria) and soil (the dominance of Alphaproteobacteria and Gammaproteobacteria) is in agreement with findings by Pradhan et al. that investigated diversity of bacterial community in chromite mine of Sukinda Valley, India ( 32 ).
The reason for dominance of the Proteobacteria strains in high heavy metal contained environments with limited nutrients might be due to their resistance mechanisms against such metals ( 29 , 33 ). Bacteria tolerant to chromium and capable of chromium or arsenic conversion, mainly belong to the Proteobacteria, Actinobacteria and Firmicutes phyla ( 25 ). In addition, similar to report by Katsaveli et al. the members of the Pseudomonadales and Enterobacteriales orders were identified in the microbial ecosystem of the Forumad area ( 28 ). Since these strains belonging to Proteobacteria are inhabitant in environment containing high amounts of heavy metals, it can be concluded that they are probably tolerance to chromium and capable to convert or remove it. Accordingly, comparing the finding in this area with those in other mine areas revealed significant similarities at phylum level. However, some differences also exist in the orders of each phylum, mostly arising from various chemical and physical properties such as metal composition and pH in these areas. Most of the studied areas have a neutral or acidic pH, while the Forumad area has an alkaline pH. According to phylogenetic trees, in the Forumad area, the microbial diversity is high, whereas the microbial biomass and OTUs frequency is low.
In this study, the similarity level of 59 OTUs (68.6% of sequences) with the type strains was less than 98.7%, showing a high percentage of unknown bacteria in this environment. These OTUs may represent new bacteria which their physiological role is unclear. Therefore, more investigations and identifications are required to obtain complete microbial feature of the Forumad area. Further, cultivated members in phyla such as Acidobacteria and Verrucomicrobia are limited in number ( 29 ).
According to our results, in the bacterial library related to the water samples, 20% of the sequences belonged to Cedecea (with similarity greater than 98%) and also, 20% belonged to Rheinheimera (with similarity greater than 98%) while these genera did not exist in the soil samples. Rheinheimera have been reported as the dominant population in the copper mine wastewater tanks ( 17 ).
In the bacterial library of the soil samples, two OTUs had 98% to 99% similarity to Ralstonia. This genus was identified in arsenic-contaminated systems and soils contaminated with radioactive materials, chromate and chromite ( 28 ). These microorganisms are oligotrophe and can be found in humid environments such as soil, river and lake. Some strains of this genus are capable to live in low nutrient environments and use various sources as energy and carbon sources. They also have the ability to degrade many toxic substrates and are able to tolerate chromate concentration up to248 g.L-1 in pH 1.3 ( 28 , 34 ). Several strains of Ralstonia have been reported to live in environments contaminated with heavy metals such as copper, nickel, iron and zinc ( 35 ).
According to EzTaxon database, there were OTUs in this library with 98% similarity to Erythromicrobium. This genus belongs to Sphingomonadales and has high tolerance to heavy metal oxides and the ability to reduce such toxic compounds. Also, species of Erythromicrobium are capable of reducing soluble tellurium (IV), which is highly toxic for microbes and other organisms ( 27 ). It may be said that these microorganisms are important for bioremediation of environment and have potential industrial and biotechnological applications.
In addition, the FMWB13 and FMWB27 OTUs showed 99% similarity to Polaromonas and Runella, respectively. Previous researches have shown that these species can contribute to bioremediation of aromatic hydrocarbon (such as naphthalene) contaminated sites ( 36 , 37 ). On the other hand, several OTUs of the water bacterial library had 95%, 98% and 99% similarity to Pseudomonas. Also, some OTUs in the soil bacterial library were 99% similar to Pseudomonas. This genus has been shown to have the ability for bioremediation of various contaminants ( 38 , 39 ).
Archaea are initially viewed as extremophiles living in harsh environments, such as hot springs and salt lakes ( 40 ). However, little information is available about the effects of heavy metals on them. Based on our findings, in the archaeal clone library, all the sequences were related to the phylum Thaumarchaeota. This phylum was proposed in 2008, distinguishing mesophilic ammonia-oxidizing archaeal (AOA) lineages from hyperthermophilic Crenarchaeota lineages ( 41 ). According to recent studies, the phylum Thaumarchaeota has been estimated to represent up to 20% and 5% of all prokaryotes in marine and terrestrial environments, respectively ( 42 ). Our results showed that the identified archaea communities (from the soil samples) belonged to Nitrososphaeraas, a genus of ammonia oxidizing archaeans in the phylum Thaumarchaeota. Based on analyses by the EzTaxon database, all the archaeal colonies were 99% similar to Candidatus Nitrososphaera gargensis Ga 9.2 adapted to environments contaminated with heavy metals. This archaea contained a heavy metal tolerance gene which responds to environmental stresses ( 43 ). Based on the findings by BLAST program of NCBI, the archaeal sequences were placed in an uncultured group and likely to present new species.
According to the studies on microbial diversity, the microbial abundance and diversity in the environment is changeable depending on environmental conditions, method and sampling time. More realistic results can be achieved by increasing the amount and number of samples. As an example, the investigation of microbial diversity in Antarctica and northern Victoria Land soils by Niederberger et al. showed the effect of soil fertility on microbial population’s diversity and frequency ( 44 ). They investigated the microbial diversity of two soil types with high and low productivity. In soils with high productivity, Proteobacteria (84℅) were dominant while in soils with low productivity Acidobacteria (68℅) and Gemmatimonas (55℅) were dominant. In other studies, the depth-dependency of archaea distribution has been mentioned and thus, Crenarchaeota were observed to be abundant in deeper soil layers and increased by increasing the soil depth. According to these studies, there is a relationship between increased number of Crenarchaeota and decreased nutrient and oxygen concentration in deep soil layers ( 43 ). Finally, based on results in this study and similar studies, composition of heavy metals in different environments can be effective on their microbial population and diversity. generally, for environmental contamination specially in the case of chromium, Proteobacteria are dominant and have important role in the bioremediation due to their certain mechanisms.
6. Conclusion
In this study, construction of clone library, among metagenomics approaches, was used to investigate the diversity of the microbial community of a chromite mine; in hope to find microbial strains may tolerant to heavy metals for application in bioremediation programs.
Our findings showed that the Forumad area can be a significant source of heavy metal resistant microorganisms which can be used for detoxification and bioremediation of regions contaminated with heavy metals, although more studies are needed. During this study and afterward, progress in NGS and bioinformatics analysis tools resulted in deeper insight and more microbial diversity information in different environments but clone library analysis gave a total and nearly complete feature of microbial diversity of a mine (at that time) in Iran and opened a new way for investigation in environmental microbiology in this field.
Future investigation of toxic substance decomposition mechanisms in these environments using NGS and metagenomics analysis can lead to identification of more heavy metal tolerant microorganisms and related genes. These genes would serve as a potential source for environmental and industrial biotechnology which is in the way.
Acknowledgments
This research was funded by the Iran National Science Foundation (INSF) with research project no. 87041055. Analyses were performed in the Industrial and Environmental Biotechnology Laboratory of the National Institute of Genetic Engineering and Biotechnology (NIGEB).
Conflicts of Interest
The authors confirm that this article content has no conflicts of interest.
Abbreviations
SOC: Sabzevar ophiolitic complex. OTUs: Operational Taxonomic Units. Cr: Chromium. Ni: Nickel. As: Arsenic. Cd: Cadmium. Co: Cobalt. Cu: Copper. Pb: Lead. V: Vanadium.
References
- Streit WR, Daniel R. Metagenomics: Methods and Protocols, Methods in Molecular Biology. Springer Science+Business Media. 2010; 668:chapter 1. DOI
- Babavalian H, Amoozegar MA, Zahraei S, Rohban R, Shakeri F, Moghaddam MM. Comparison of bacterial biodiversity and enzyme production in three hypersaline lakes; Urmia, Howz-Soltan and Aran-Bidgol. Indian J Microbiol. 2014; 54(4):444-449. DOI
- Datta S, Rajnish KN, Samuel MS, Pugazlendhi A, Selvarajan E. Metagenomic applications in microbial diversity, bioremediation, pollution monitoring, enzyme and drug discovery. A review. Environ Chem Lett. 2020;1-13. DOI
- Kepel BJ, Gani MA, Tallei TE. Comparison of Bacterial Community Structure and Diversity in Traditional Gold Mining Waste Disposal Site and Rice Field by Using a Metabarcoding Approach. Int J Microbiol. 2020; 2020DOI
- Rajendhran J, Gunasekaran P. Strategies for accessing soil metagenome for desired applications. Biotechnol Adv. 2008; 26(6):576. DOI
- Ferrer M, Beloqui A, Timmis KN, Golyshin PN. Metagenomics for Mining New Genetic Resources of Microbial Communities. J Mol Microbiol Biotechnol. 2009; 16:109-123. DOI
- Kumar Awasthi M, Ravindran B, Sarsaiya S, Chen H, Wainaina S, Singh E, et al. Metagenomics for taxonomy profiling: tools and approaches. Bioengineered. 2020; 11(1):356-374. DOI
- Hiraoka S, Yang C-c, Iwasaki W. Metagenomics and bioinformatics in microbial ecology: current status and beyond. Microbes Environ. 2016;ME16024. DOI
- Staley C, Sadowsky MJ. Application of metagenomics to assess microbial communities in water and other environmental matrices. J Mar Biolog Assoc. U.K. 2016; 96(1):121-129. DOI
- Liu Z, DeSantis TZ, Andersen GL, Knight R. Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers. Nucleic Acids Res. 2008; 36:1-11. DOI
- Johnson JS, Spakowicz DJ, Hong B-Y, Petersen LM, Demkowicz P, Chen L, et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat Commun. 2019; 10(1):1-11. DOI
- STACKEBRANDT E, GOEBEL BM. Taxonomic Note: A Place for DNA-DNA Reassociation and 16s rRNA Sequence Analysis in the Present Species Definition in Bacteriology. Int J Syst Evol. 1994; 44:846-849. DOI
- Sánchez-Reyes A, Folch-Mallol JL. Metagenomics-Based Phylogeny and Phylogenomic. Phylogenetics: IntechOpen. 2019. DOI
- Otari M, Dabiri R. Geochemical and environmental assessment of heavy metals in soils and sediments of Forumad Chromite mine, NE of Iran. J Mining Environ. 2015; 6(2):251-261. DOI
- J Z, MA B, JM T. DNA recovery from soils of diverse composition. Appl Environ Microbiol. 1996; 62:316-322. DOI
- Sambrook J, all e. Moleacular cloning: A laboratory manual. Cold Spring Harbor Laboratory Press: NY; 2001.
- Khan S, Hesham AE-l, Ahmad A, Houbo S, Daqiang C. Physio-chemical characteristics and bacterial diversity in copper mining wastewater based on 16S rRNA gene analysis. Afr J Biotechnol. 2010; 9:7891-7899. DOI
- Huber T, Faulkner G, Hugenholtz P. Bellerophon; a program to detect chimeric sequences in multiple sequence alignments. Bioinformatics. 2004; 20:2317-2319. DOI
- Chun J, Lee J-H, Jung J, Kim M, Kim S, Kim BK, et al. EzTaxon: a web-based tool for the identification of prokaryotes based on 16S ribosomal RNA gene sequences. Int J Syst Evol Microbiol. 2007; 57:2259-2261. DOI
- Kumar s, G S, D P, K T. MEGA-CC: Computing Core of Molecular Evolutionary Genetics Analysis Program for Automated and Iterative Data Analysis. Bioinformatics. 2012; 28:2685-2686. DOI
- MA L, al e. Clustal W and Clustal X version 2. Bioinformatics 2007; 23:2947-2948. DOI
- Felsenstein j. Phylogenies and the comparative method. Am. Nat. 1985;1-15. DOI
- Qing H, Hong-yan Q, Jing-hai Z, Hong-xun Z. Bacterial diversity in soils around a lead and zinc mine. J Environ Sci. 2007;74-79. DOI
- Hemme CL, Deng Y, Gentry TJ, Fields MW, Wu L, Barua S, et al. Metagenomic insights into evolution of a heavy metal-contaminated groundwater microbial community. ISME. 2010; 4:660-672. DOI
- Sheik CS, Mitchell TW, Rizvi FZ, Rehman Y, Faisal M, Hasnain S, et al. Exposure of Soil Microbial Communities to Chromium and Arsenic Alters Their Diversity and Structure. PLoS ONE. 2012; 7(6)DOI
- Zhen Z, Wang S, Luo S, Ren L, Liang Y, Yang R, et al. Significant impacts of both total amount and availability of heavy metals on the functions and assembly of soil microbial communities in different land use patterns. Front Microbiol. 2019; 10:2293. DOI
- YURKOV VV, BEATTY JT. Aerobic Anoxygenic Phototrophic Bacteria Microbiol. Mol Biol Rev. 1998; 62:695-724. DOI
- Katsaveli K, Vayenas D, Tsiamis G, Bourtzis K. Bacterial diversity in Cr(VI) and Cr(III)-contaminated industrial wastewaters. Extremophiles-Springer. 2012; 16:285-296. DOI
- Rastogi G, Stetler LD, Peyton BM, Sani RK. Molecular Analysis of Prokaryotic Diversity in the Deep Subsurface of the Former Homestake Gold Mine, South Dakota USA. Microbiol. 2009;371-384. DOI
- Dhal PK, Islam E, Kazy SK, Sar P. Culture-independent molecular analysis of bacterial diversity in uranium-ore/-mine waste-contaminated and non-contaminated sites from uranium mines. Biotech. 2011; 1:261-272. DOI
- Lusa M, Knuutinen J, Lindgren M, Virkanen J, Bomberg M. Microbial communities in a former pilot-scale uranium mine in Eastern Finland–Association with radium immobilization. Sci Total Environ. 2019; 686:619-640. DOI
- Pradhan SK, Singh NR, Thatoi H. Metagenomics insights into Cr (VI) effects on structural and functional diversity of bacterial community in chromite mine soils of Sukinda Valley, Odisha. Can J Biotech. 2017; 1(Special):268. DOI
- Pradhan SK, Singh NR, Rath BP, Thatoi H. Bacterial chromate reduction: a review of important genomic, proteomic, and bioinformatic analysis. Crit Rev Environ Sci Technol. 2016; 46(21-22):1659-1703. DOI
- Ryan MP, Pembroke JT, Adley CC. Ralstonia pickettii in environmental biotechnology potential and applications. J Appl Microbiol. 2007; 103:754-764. DOI
- Konstantinidis K, Isaacs N, Fett J, Simpson S, Long D, Marsh T. Microbial Diversity and Resistance to Copper in Metal-Contaminated Lake Sediment. Microb Ecol. 2003; 45:191-202. DOI
- Jeon CO, W P, WC G, EL M. “Polaromonas naphthalenivorans sp. nov., a naphthalene-degrading bacterium from naphthalene-contaminated sediment”. Int J Syst Evol. 2004; 54:93-97. DOI
- Shipeng LU, Lee JR, Ryu SH, Chung BS, Jeon W-SCCO. Runella defluvii sp. nov., isolated from a domestic wastewater treatment plant. IJSEM. 2007; 57:2600-2603. DOI
- Caister Academic Press. ISBN. Genomics and Molecular Biology: Pseudomonas; 2008. DOI
- Hirota K, K Y, K N, Y N, H O, I Y. Pseudomonas toyotomiensis sp. nov., a psychrotolerant facultative alkaliphile that utilizes hydrocarbons. Int J Syst Evol Microbiol. 2011;1842-1848. DOI
- Rampelotto PH. Extremophiles and extreme environments. MDPI. 2013. DOI
- Brochier-Armanet C, Boussau B, Gribaldo S, Forterre P. Mesophilic Crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota. Nat Rev Microbiol. 2008; 6(3):245-252. DOI
- Hong J-K, Kim H-J, Cho J-C. Novel PCR primers for the archaeal phylum Thaumarchaeota designed based on the comparative analysis of 16S rRNA gene sequences. PloS One. 2014; 9(5):e96197. DOI
- Radeva G, Kenarova A, Bachvarova V, Flemming K, Popov I, Vassilev D, et al. Phylogenetic Diversity of Archaea and the Archaeal Ammonia Monooxygenase Gene in Uranium Mining-Impacted Locations in Bulgaria. Archaea. 2014;1-10. DOI
- Niederberger TD, McDonald IR, Hacker AL, Soo RM, Barrett JE, Wall DH, et al. Microbial community composition in soils of Northern Victoria Land, Antarctica. Environ Microbiol. 2008; 10(7):1713-1724. DOI