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Prokaryotic diversity of acid mine drainage ponds in ore enrichment plant

Prokaryotic diversity of acid mine drainage ponds in ore enrichment plant

Yağmur TOPTAŞ1, Ahmet ÇABUK2, 3

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1 Department of Biology, Graduate School of Natural and Applied Sciences, Eskisehir Osmangazi University, 26480, Eskisehir, Turkey

2 Department of Biotechnology and Biosafety, Graduate School of Natural and Applied Sciences, Eskisehir Osmangazi University, 26480, Eskisehir, Turkey;

3 Department of Biology, Faculty of Arts and Science, Eskisehir Osmangazi University, 26480, Eskisehir, Turkey

Corresponding author: yagmurtoptas@gmail.com (Y. Toptaş)

Tel.: +90 222 239 37 50×2757; fax: +90 222 239 35 78.

Abstract

The biodiversity of acidophilic prokaryotes was determined in three AMD ponds (pH 2.7-6.5) in Turkey (İzmir-Halıköy antimony ore enrichment plant) using 16S rRNA cloning and denaturing gradient gel electrophoresis methods. Water samples were taken two times in March 2014 and June 2015. The microbial diversity identified with the techniques used includes species such as Acidiphilium angustum, Acidocella sp., Ferroplasma acidiphilum, Acidithiobacillus ferriphilus, Acidithiobacillus ferrivorans, Acidiphilium rubrum, Thiomonas sp., Acidiphilium multivorum, Acidiphilium cryptum, Ferrovum myxofaciens, Acidocella aluminiidurans. In addition to, it has been determined that biodiversity is variable in the operating mine pools. Aciditihobacillus ferriphilus, Acidiphilium angustum, and Acidiphilium rubrum are new records for Turkey.

Keywords: acidic mine drainage, acidophiles, prokaryotic diversity, Turkey

Introduction

Acid mine drainage (AMD) is the largest environmental problem caused by normally associated with mining activities (Garcia-Moyano et al. 2015). The mining wastewater is defined by properties such as low pH, high metal ions (e.g., iron, nickel, copper) and mineral concentrations. Acidophilic microorganisms living in this habitat are very interesting because of their adaptability to extreme pH values, their metabolic diversity, and their ability to be used in biomining applications. Especially, due to their availability in biomining and bioremediation applications, it is important to identify the acidophiles living in AMD. As determined in previous studies, the AMD microbial community changes over time (McGinnes and Johnson 1993; Edwards et al. 1999; Volant et al. 2014 ). The variety of microbial community is attached to seasonal changes and environmental conditions in AMD. (Auld et al. 2017).

Classical microbial ecology methods remain limited in determining microbial diversity. Therefore, culture-independent methods such as 16s rRNA gene cloning, fluorescent in situ hybridization (FISH) and denaturing gradient gel electrophoresis (DGGE) are often used to investigation the diversity of microbial community that adapts to this unique environments (Gonzalez-Toril et al. 2003; Nicomrat et al. 2006; Garcia-Moyano et al. 2015). Acidophilic chemolithotrophs such as Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillium ferrooxidans have been identified in AMD which extremely low pH and high concentrations of iron, sulfates and other heavy metals (Edwards et al. 1999; Kuang et al. 2013). At the same time, the investigation of microbial community by molecular methods is difficult because of the inhibition of PCR by metals such as Fe and Cu (Nicomrat et al. 2006). For the reason, DGGE and 16s rRNA gene cloning methods are used together to support each other in determining the microbial diversity of AMD.

The aim of this research was to determine the acidophilic microbial community of acid mine drainage in ore enrichment plant Halıköy, İzmir (Turkey). Our study area in Halıköy is within the Menderes Massif in western Turkey. The antimony mine was discovered in 1870 and continued to operate until 1918 in Halıköy area. After a long-standing period, production began again in 1974 (Akçay et al. 2006). Our results are the first knowledge about the microbial community of the selected AMD area.

Material and methods

Site description and sample collection

The water samples were collected from the operating antimony mine, ore enrichment plant Halıköy site (38°5’28.09”N, 28°10’09.6”E) in İzmir, Turkey (Fig. 1), in two different seasons (March 2014 and June 2015). The samples were taken three different points from mine area as drainage water (sample #1 and sample #4), iron oxide pool water (sample #2 and sample #5), and stationary water before iron oxide pool (sample #3 and sample #6) (Fig. 2). Water samples were taken in sterile Duran bottles and were filtered from 0.2 um GTTP filter. In situ measurements for pH were made using a WTW Multi350i/SET (WTW, Germany). Metal concentrations of water samples were measured by inductively coupled plasma atomic emission spectrometry (ICP-AES) using a PerkinElmer model 3100.

DNA isolation and 16S rRNA gene amplification

DNA isolations were performed following the procedure explained by Cifuentes et al. (2000) and Nogales et al. (1999) as modified. We used the primer set 27F (AGAGTTTGATCMTGGCTCAG)-1387R (GGGCGG(AT)GTGTACAAGGC) and 20F (AGAGTTTGATC(AC)TGGCTCAG)-915R (GTGCTCCCCCGCCAATTCCT) for bacteria and archaea, respectively.

PCR cycles were as follows: 1 cycle at 95 °C for 5 min, 30 cycles at 95 °C for 30 second, 1 min at the corresponding annealing temperature 55 °C and 62 °C (for bacteria and archaea, respectively) and 72 °C for 1.5 min, and a final extension step at 72 °C for 10 min.

16S rRNA gene cloning

The PCR products were cloned using the pGEM-T easy vector system II and colony PCRs were set up with 27F and 1387R; 20F and 907R primer sets of selected colonies, for bacteria and archaea, respectively. Similar profiles were determined by amplified ribosomal DNA restriction analysis (ARDRA) in the 16S rRNA gene libraries. Clones were divided into categories (3 h, 37°C) based on pattern generated by the restriction enzymes MspI and HaeIII (5 units each).

DGGE

Amplification of the 16S rRNA gene was carried out with specific primers for DGGE analysis. Primer set including 344F-GC (CGCCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCGACGGGGCGCAGCAGGCGCGA) and 907R (CCGTCAATTCCTTTGAGTTT) was used for the archaeal gene amplification while for the bacterial gene, the forward primer, 341F-GC (CGCCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCGCCTACGGGAGGCAGCAG) in combination with 907R were used (Muyzer et al., 1993). DGGE PCR condition for bacteria: 1 cycle at 94 °C for 5 min, 1 min at 65 °C and 3 min at 72 °C and 9 cycles at 94 °C for 1 min, 1 min at the annealing temperature was decrease 64- 55 °C and 72 °C for 3 min, and 1 cycle at 94 °C for 5 min, 1 min at 55 °C and 3 min at 72 °C and a final step 94 °C for 5 min, 1 min at 55 °C and 10 min at 72 °C. DGGE PCR condition for archaea: 1 cycle at 94 °C for 5 min, 29 cycles at 94 °C for 3 sec, 56 °C for 45 sec, 72 °C for 2 min, and 1 cycle at 94 °C for 30 sec, 56 °C for 45 sec, 72 °C for 7 min. The PCR products were purified with the Wizard SV Gel and PCR Clean-Up System (Promega, Italy).

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Denaturing gradient gel electrophoresis (DGGE) was performed with the DCode Universal Mutation Detection System (Bio-Rad Laboratories, Inc.). PCR product was loaded on 1 mm thick 8% (w/v) polyacrylamide (37.5: 1 acrylamide: bisacrylamide) gels containing a 45-60% linear denaturing gradient. Gels were run in 1X TAE buffer at 60°C and 90 V for 18 h. Gels were stained in 1X TAE buffer containing ethidium bromide solution (1 μg/ ml) and photographed under UV transillumination.

Each band in different positions was cut with a sterile lancet from the polyacrylamide gel and was stored at 37 °C in solvent buffer (ammonium acetate 5M, magnesium acetate 10 mM, EDTA (pH 8.0) 1mM, SDS 0.1%) during overnight and were isolated of DNA fragments. The DNA fragments were used re-amplification with same primer pairs without GC clamps and were sequenced.

Accession numbers and construction phylogenetic tree of nucleotide sequences

Multiple gene alignments were applied using MUSCLE software. Phylogenetic trees were made using MEGA version 7 and the neighbor-joining method (Saitou and Nei 1987). The 16S rRNA gene sequences and results of DGGE analyses were uploaded into the GenBank Database.

Result

Characteristics of site and samples

The sampling site is antimony mine site being operated. The AMD samples were characterized by acidic pH values ranging from 2.7 to 6.5 and high concentrations of dissolved metals (Table 1). The sample points show the typical orange and red colors of dissolved ferric iron as shown in Figure 1. It was determined that the samples had high iron, zinc, lead and manganese ratios. Treatment and neutralization studies of outlet water caused the pH value to increase and iron concentration to decrease between two sampling times (sample #5). This pH change also affected the prokaryotic diversity at the sample site (Table 1).

Cloning

Clone library technique offers the opportunity to do very sensitive taxonomic studies. By this method, uncultured and unspecified microorganisms are also possible to define (Sanz and Kochling 2007). The clones from sample #1 and #3 YT_K1, YT_2, YT_K12, YT_K14, YT_K16 matched with an uncultured bacterium (%99), an uncultured archaeon (%97), Acidithiobacillus ferrivorans (%99), Acidithiobacillus ferriphilus (%99), and Acidiphilium rubrum, respectively. According to ARDRA of the plasmid insert, it has been determined that there are 4 and 14 different profiles from sample #2 and #5 (same points, different periods) coded samples taken in March 2014 and June 2015, respectively (Fig 3). The sequence of clones (from water samples #2) YT_K3, YT_K4, YT_K7, and YT_K8 showed 99% similarities with Acidiphilium sp., Acidithiobacillus ferriphilus, Acidocella sp., Acidiphilium angustrum, respectively. Clones from water sample #3, YT_K12 and YT_K13 matched with Acidithiobacillus ferrivorans (similarity 99%), YT_K14 and YT_K16 matched with Acidithiobacillus ferriphilus, Acidiphilium rubrum (similarity 99%), respectively. The archaeal profile was only determined on AMD samples #1 and #3. According to the results of sequence analysis the clones YT_K11, and YT_K20 matched with Ferroplasma acidiphilium (similarity 99%), and clone YT_K9 showed 99% similarities with Thermoplasmatales archaeon. Other clones from water samples #4 and #6 showed 99% similarities with Acidiphilium sp. and Thiomonas sp. The sequencing results of the clones were given in Table 3.

DGGE

DGGE analyses were performed with each different sample to determine the level of microbial diversity in the mine area. (Fig 4). Samples collected at different times from the same sample location were determined to have different profiles. Especially, due to pH change, it was found that bacterial diversity quite different sample #5 from sample #2. Blast analyses of DGGE bands sequences are given in Table 3. Archaeal diversity was determined only in sample #1 and sample #3. The sequence of bands YT_D1, YT_D2, YT_D3, YT_D4, and YT_D5 showed similarity with uncultured archaeon clones, as a show that in Table 3. Differences were observed in the DGGE profiles of water samples taken at different times from the same sampling points. Bacterial diversity of sample #4 was determined to have more from sample #1. According to sequence analysis results, there are bands matched with Ferrovum myxofaciens, Acidithiobacillus ferrooxidans, Acidithiobacillus ferrivorans, Acidithiobacillus ferriphilus and uncultured Acidithiobacillus sp. in sample #1. In the case of water sample #4, it was determined that the majority of the species are Acidocella (Table 3). Although samples #2 and #5 were taken from the same spot, it was thought that the change in pH at sample #5 caused the formation of different profiles. Bands at sample #5 were showed similarity with Acidocella aluminiidurans, uncultured Acidocella sp. and uncultured Acidiphilium sp. In sample #3, bacterial diversity is less than in sample #6. The band of sample #6, it was determined to match with Thiomonas sp. (Table 3).

Accession numbers and construction phylogenetic tree of nucleotide sequences

16S rRNA gene sequences were deposited in GenBank under accession numbers MH057089-H057162. In order to determine the phylogenetic group, the phylogenetic tree was constructed with sequences obtained by 16 rRNA clone library and DGGE analyses. (Fig. 5 and 6).

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Discussion

Determining of communities in AMD provides important clues in terms of the diversity and functions of these organisms with the development of molecular approaches. Furthermore, the development of sequencing technologies is rare in acidic environments allowing the identification of numerous taxa found (Kuang et al. 2013; Goltsman et al. 2015).

The pH value and metal concentrations of the AMD ponds seem to be suitable for existence in the determined species. Especially, high iron concentration is determinant for the life of species such as Acidithiobacillus ferrivorans, Aciditihobacillus ferriphilus. Mendez and coworkers have determined Acidithiobacillus ferrivorans in similar properties samples (pH 2.7, Fe: 38.100 mg kg -1) (Mendez et al. 2008). One of the sequences identified in the study of microbial diversity of Xiang Mountain sulfide mine was matched with Ferrovum myxofaciens, which was recently isolated from an abandoned copper mine (pH 3.0, Fe: 100.6 mg L-1) (Hao et al. 2010). Acidiphilium sp. was determined by community composition analysis in acid mine drainage from Fankou Pb/Zn mine, China (pH 1.9, Fe 1240 mg L-1) (Chen et al. 2015).

Autotrophic and heterotrophic groups were identified from selected sample points in this study. It is noteworthy that archaea domain members cannot be determined from samples #4 and #6 in June 2015 while the archaea were determined in March 2014 (samples #1 and #3). It is thought that this may be due to the continuing effects of the mining activity. Changes in the environment created by anthropogenic effects are rapidly affecting microbial diversity. Ferroplasma spp., which was identified in this study has been determined to dominant after the period of the acidification processes of mine wastes (Chen et al. 2013; Chen et al. 2014).

As seen in figure 7, the molecular techniques used in this study differed in determining prokaryotic diversity in AMD ponds. As one of the reasons for this, some of the technical difficulties of the methods used can be shown. While sequencing over a short region of DNA by the DGGE method, the cloning longer base chain can be evaluated. With all of these drawbacks, both methods complement each other’s deficiencies so that can determine the prokaryotic diversity of AMD ponds to a significant extent. For example, Ferroplasma sp., Thiomonas sp. species could be identified only by 16S cloning, while Ferrovum sp. could be identified only by DGGE method. Other less frequently detected bacterial taxa the heterotrophic growers Thiomonas spp. (Chen et al. 2016) that has been isolated was not detected by molecular techniques, probably reflecting its low abundance (Bruneel et al. 2005).

Gonzalez-Toril and collaborates were studied by DGGE using 16S rRNA and by 16S rRNA gene amplification for research molecular ecology an extreme acidic Tinto River (Spain). Comparative sequence analysis of DGGE bands determined the entity of the respective microorganisms like Leptospirillum spp., Acidithiobacillus ferrooxidans, Acidiphilium spp., Ferrimicrobium acidiphilum, Ferroplasma acidiphilum, and Thermoplasma acidophilum (Gonzalez-Toril et al. 2003). Aytar and coworkers have identified prokaryotic diversity in two different AMD sites (Balya and Çan) in Turkey (Aytar et al. 2015). Some species identified in this study were as Acidithiobacillus sp., Leptosipirillum sp., Ferooplasma sp. Sağlam and colleagues determined bacterial diversity in the Acısu effluent with cloning 16s rRNA sequences. The bacterial population was identified to occur Acidithiobacillus ferrivorans, Ferrovum myxofaciens, Leptospirillum ferrooxidans, Acidithiobacillus ferrooxidans, Acidocella facilis, Acidocella aluminiidurans, Acidiphilium cryptum, Acidiphilium multivorum, Acidithiobacillus ferrivorans, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Acidiphilium cryptum (Sağlam et al. 2016).

Alphaproteobacteria (Acidiphilium, Acidocella) (Liu et al. 2011; Falagan et al. 2014), Betaproteobacteria (Thiomonas, Ferrovum), (Mendez et al. 2008; Johnson et al. 2014), Acidithiobacillia (Acidithiobacillus) (Williams and Kelly 2013) are seen in other studies. Betaproteobacteria, mostly belonging to the ‘Ferrovum’ genus, was clearly predominant in the community below middle pH conditions, whereas Alphaproteobacteria, Euryarchaeota, Gammaproteobacteria, and Nitrospira exposed a powerful adaptation to more acidic conditions (Kuang et al. 2013).

As a result of matches, it has been determined that some sequences are similar to those of Aciditihobacillus ferriphilus (Nunez et al. 2017), Acidiphilium angustum, and Acidiphilium rubrum (Auld et al. 2013). These species are new records for Turkey. The iron-oxidizing acidithiobacilli Acidithiobacillus ferriphilus was also isolated from different global locations such as metal-rich waters sample deep within the mine (Kay et al. 2014). The type strain M20T was isolated from a ponds in a geothermal area of Montserrat (pH 1.5-3.0) (West Indies) that live optimally pH 2.0 and 30 °C of temperature (Atkinson et al. 2000). It was determined later that this strain separated from other acidithiobacilli (Falagan and Johnson 2016). The clones and DGGE bands sequences showed to match the most Acidiphilium genus. The mesophilic and obligately acidophilic bacteria Acidiphilium angustum grow in the pH range of 2.0-5.9. The clone YT_K8 matched with Acidiphilium angustum (99% similarity) was obtained from water sample #2 (pH 2.9). Auld and coworkers have isolated Acidiphilium rubrum from an AMD site in Copper Cliff, Ontario (Auld et al. 2013). The isolate was isolated from AMD water at pH 2.5, similar to the water sample (pH 2.7) in which identified YT_K16.

Conclusion

Future studies will focus on the roles of these species on the biogeochemical cycles of the region where microbial diversity is determined. The AMD is also likely to contain new species. To better understand community dynamics in acid formation, more studies are needed to identify predominant species in AMD environments.

Acknowledgment

This study is based partly on the Ph.D. thesis of Y. Toptaş.

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