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Poor nutrient availability in opencast coalmine influences microbial community composition and diversity in exposed and underground soil profiles
Applied Soil Ecology 152 (2020) 103544
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Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil
Short communication
Poor nutrient availability in opencast coalmine influences microbial community composition and diversity in exposed and underground soil profiles Sohini Banerjeea,b,1, Arijit Misraa, Abhijit Sara, Srikanta Pala, Shibani Chaudhuryb, Bomba Dama,
T
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a
Microbiology Laboratory, Department of Botany (DST-FIST & UGC-DRS Funded), Institute of Science, Visva-Bharati (A Central University), Santiniketan, West Bengal 731235, India b Department of Environmental Studies, Institute of Science, Visva-Bharati (A Central University), Santiniketan, West Bengal 731235, India
A R T I C LE I N FO
A B S T R A C T
Keywords: Opencast coalmine Physicochemical properties Microbial population Vertical soil sampling Proteobacteria
Microbial community composition and geochemical properties in opencast mines in general, and particularly along depth is poorly understood. Here, we attempt to understand the change in these features in an active opencast coalmine in Bera, Jharkhand, India, using soil from the surface of an excavated coalmine; four samples from 2, 4, 6 and 8 m below the surface layer, and an exposed surface two meters above the soil. The previously exposed, surface, and two meters below samples have circum-neutral pH (7.7, 6.5 and 6.1 respectively), but it drops to 4.7 in the 8-m underground sample. Soil is nutritionally poor with low total organic carbon (0.03–2.66%), available nitrogen (0.0001–0.0034%), and heterotrophic microbial load (7.6 × 104–3.1 × 107) having lowest values in samples beyond two meters' depth. Amplicon sequences of the V1-V2 hyper-variable region of 16S rRNA gene of the previously exposed, surface, and two meters below samples show a low microbial diversity with 313, 275 and 118 operational taxonomic units respectively. Proteobacteria was the predominant phyla across all samples (97.44%–52.09%) with betaproteobacterial members such as Hydrogenophilales and Rhodocyclales being abundant in previously exposed soil (65.5%), but with negligible representation (0.5%–1.9%) in the other two. Distribution of Alphaproteobacterial and Gammaproteobacterial members was in reverse order. Thus, the study describes how poor nutrient availability in opencast coalmine influences microbial community composition and diversity in exposed and underground soil profiles.
1. Introduction Coal mining is a destructive operation which leads to deforestation, dust and noise pollution, land subsidence, erosion, accumulation of overburden dumps, and contamination of water bodies. Mine soil quality is site specific and differs from one another due to geology of the site, climatic factors and differences in mining techniques. Opencast mining has two-fold detrimental effect, first when the topsoil at miningsite is removed, and second when the overburden dumps are deposited in unmined areas leading to poor soil quality and loss of biodiversity on temporal and spatial scales (Masto et al., 2011; Saini et al., 2016). Coal mining is also one of the largest reasons for heavy metal pollution (Masto et al., 2011; Silva et al., 2011). To assess mine soil health, several parameters related to their physical, chemical, and biological properties have been used as indicators and these information have helped to develop reclamation strategies of both active and abandoned
mines around the world (Das and Chakrapani, 2011; Pasayat and Patel, 2015). Among living systems, microorganisms are preferred as indicators as they contribute in every biogeochemical cycle (Nielsen et al., 2002). Soil microbial communities may vary even by millimeters, both horizontally and vertically, depending on abiotic factors like pH, organic carbon, available nitrogen, moisture content, salinity, and its texture (Armitage et al., 2012; O'Brien et al., 2016; Shen et al., 2015). They have also been advocated to be suitable in remediation processes of contaminated soil and water. Bacterial diversity and its role in soil health is predominantly studied near the topsoil (~15 cm depth), with those at deeper soil horizons being sparsely studied because of the low biomass densities and metabolic activities (Ghiorse and Wilson, 1988). Although exponential decrease in microbial cell count with depth has been reported, some active cells do remain in deeper soil horizons that are adapted to limited nutrients and energy (Hartmann et al., 2009;
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Corresponding author. E-mail address: [email protected] (B. Dam). 1 Present Address: Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine, Houston, Texas, USA. https://doi.org/10.1016/j.apsoil.2020.103544 Received 22 September 2019; Received in revised form 25 January 2020; Accepted 5 February 2020 0929-1393/ © 2020 Published by Elsevier B.V.
Applied Soil Ecology 152 (2020) 103544
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total nitrogen (TN) was measured using Kjeltek method (FOSS, Denmark) (Bremner, 1960). Organic carbon (OC) was estimated by Walkley-Black titration method (Walkley, 1947). Ion-exchange chromatography (Metrohm Basic IC plus 783) was used to assess the presence of water-soluble anions (SO42−, NO3−, NO2−, Cl−, Br−, F−, PO4−2). Elemental analyses were carried out using Atomic Absorption Spectroscopy facility at Bose Institute, Kolkata, India (iCE 3000 Series, Thermo Fisher Scientific, USA). Heavy metals (Ca, Mg, As, Cd, Co, Cr, Fe, Ni and Pb) were estimated from ~0.2 g soil sample after tri-acid (HF–HNO3–HClO4) digestion (EPA, 1996). Flame Photometer was used to measure Na+ and K+ (Jackson et al., 1976). A Spearman correlation analysis was performed using log-normalized values in GraphPad Prism-7.0.
Turner et al., 2017). Even in open cast coalmines which involve digging deep underground, ecological studies performed have mostly focused on the microbial diversity of either stockpiles or reclaimed land. Thus, objective of the present study was to understand relationship between geochemical properties and microbial distributions in exposed and underground soil profiles of an active excavated coalmine, Bera in Jharia, Jharkhand, which is one of the oldest and largest coal producing mines in India, but is not explored in term of its microbial diversity and richness. 2. Materials and methods 2.1. Site description and sampling
2.3. Microbial enumeration
Bera Colliery (23° 45′ 56″ N, 86° 25′ 44.7″ E), in the eastern flank of Jharia coalfield, is an active opencast mine that started operations in early nineteenth century (Gee, 1940). Soil samples were collected in April 2013, from different horizons of the excavated coalmine. This includes the surface layer as on the date of sampling; a coal seam two meters above surface from the wall that was exposed due to previous mining operation almost one year ago; and eight meters below the surface layer at depths of 2 m intervals (Fig. 1). Samples were named accordingly as B.2A, B.S, B.2B, B.4B, B.6B and B.8B with, ‘B’ in prefix standing for Bera, ‘S’ for the surface layer, and numbers for meters above ‘A’ or below ‘B’ the surface in suffix. For this, a core drilling rig hydraulic machine generally used by the coal miners to estimate the next layer of coal seam was used and its tip was thoroughly cleaned with 70% alcohol after every drilling. Samples were collected aseptically in sterile 50 mL falcon tubes and brought to the laboratory on ice and stored at 4 °C (for culture-based work) or −20°C (for DNA isolation) until further use.
Viable aerobic bacterial load was enumerated by plate count using 0.1 mL of the appropriately diluted samples (in saline water, 0.9% NaCl) on Luria-Bertani agar plates followed by incubation at 30 °C for 48 h.
2.4. DNA extraction, sequencing and analysis Total soil DNA was extracted from 0.5 g sample using the Fast DNA SPIN Kit for Soil (MP Biomedicals, Santa Ana, CA, USA), according to manufacturer's instructions. The V1-V2 hyper-variable region of 16S rRNA gene was amplified from the metagenomic DNA using appropriately bar-coded and adaptor ligated forward (5′-AGAGTTTGATCITGGCTCAG-3′) and reverse (5′-CTGCTGCCTCCCGTAGG-3′) primers following standardized protocol (Banerjee et al., 2018). Amplicon libraries were sequenced at Genotypic Inc., Bangalore, India on Ion PGM 318 Chip using 400 bp chemistry (Life Technologies, USA). Sequences were analyzed using the standalone installation of QIIME1 (Caporaso et al., 2010) and USEARCH (Edgar, 2010) on Biolinux following our lab's standardized pipeline (Banerjee et al., 2018). QIIME was used to estimate alpha and beta diversity (Lozupone and Knight, 2005) and was visualized using Principal Coordinate Analysis (PCoA) plot. Statistical analyses were performed on R 3.2.1 (cran.rproject.org), and figures generated using GraphPad Prism 7.
2.2. Geochemical analyses pH was measured at a 1:2.5 (wt/vol) sample-to-distilled-water ratio at 25 °C using a portable multi-parameter instrument (Hanna Instruments, USA). For all geochemical analyses, samples were dried at 105 °C overnight and thoroughly grated using a mortar and pestle before passing through a 200-mesh sieve. Available nitrogen (AN), and
Fig. 1. Sampling site. Bera coalmine, located in Jharkhand state of India. Samples are labelled as, B.S for surface layer as on the date of sampling (April 2013); B.2A is the soil scraped from two meters above surface from the wall, exposed due to previous mining operation; and B.2B represents soil drilled out from 2 m below the surface layer. A core drilling rig hydraulic machine generally used by the coal miners to estimate the next layer of coal seam was used. 2
Applied Soil Ecology 152 (2020) 103544
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Table 1 Soil physicochemical properties of B.2A, B.S, and B.2B. Organic carbon (OC), available nitrogen (AN), and total nitrogen (TN) are expressed in percentage. All other values except pH are expressed in ppm.
pH OC AN TN F− Cl− Br− NO32− SO42− Na+ K+ Ca2+ Mg2+ Fe2+ Pb2+ Cr3+
B.2A
B.S
B.2B
7.71 1.17 0.0025 0.76 1.87 715.86 4.12 360.7 143.43 1445.40 9074.57 5395.93 6065.30 4547.13 665.10 713.00
6.54 2.66 0.0034 0.14 1.02 28,310.21 BDL 656.44 345.44 1242.47 8124.33 3855.93 5313.00 2595.40 162.77 519.67
6.1 1.88 0.00028 0.13 4.21 11,210.87 8.41 15.99 196.16 1350.73 7957.50 4521.40 5286.53 1476.23 161.10 367.83
BDL = below detection level.
2.5. Data deposition Raw sequence reads were deposited in fastq format to the National Center for Biotechnology Information Sequence Read Archive under BioProject accession number PRJNA491301. The project includes seven BioSamples, from two coalfields of Jharia (India), four from Tasra Colliery (not used in this study), and three from Bera Colliery (SAMN10069354, SAMN10069355, SAMN10069356) used in this study.
Fig. 2. (a) Sequence read statistics and diversity indices. (b) Venn diagram showing shared and unique OTUs in different samples of Bera Colliery. Numbers in brackets show the percent overlap.
3.2. Microbial diversity along soil depth To get a clear representation of the microbial taxa, amplicon sequencing of the V1-V2 hyper-variable region of 16S rRNA gene was performed and a total of 716,960 raw sequences were generated for the three soil samples. After pre-processing, 485,085 filtered sequences with Phred quality score of Q25, and average length of 200–350 bp was used for downstream analyses (Fig. 2a). None of the obtained sequences corresponds to OTUs of Archaea or Eukarya. Although a high sampling coverage (~99%) was obtained (Fig. S3), the number of OTUs was low in general, with highest value of 313 in B.2A followed by 275 in B.S, and a mere 118 in B.2B. Alpha diversity was also highest for B.2A as implied by the higher values of Chao1 (Fig. S4), and Shannon and Simpson indices (Fig. 2a). Venn-diagram using shared and unique OTUs shows that B.2A has almost 4.5 times the number of unique species as compared to B.2B (Fig. 2b). Uniqueness of the microbial composition in B.2B is also evident from the very few shared OTUs with B.2A (3.4%) and none with B.S (0%). The OTUs across all samples were represented by eleven distinct phyla (Table S2) with only five being in the top 1%. Percentage of unassigned OTUs was quite low (≤2%). Some assemblages of yet-to-be cultivated members, like OP11, TM7, and WPS-2 were also identified. Proteobacterial members were most predominant across all samples with highest representation in B.2B (97.44%), followed by B.2A (90.57%) and B.S (52.09) (Fig. 3a). Interestingly, in B.S, Actinobacteria comprises about 45% of the total population. Other phyla like Bacteroidetes, Chloroflexi and [Thermi] are in minor representations (≤1%) (Table S2). Distribution of proteobacterial members have an interesting trend, with Betaproteobacteria being the dominant class (65.5%) in B.2A, but with negligible representation in B.S (1.9%), and further more in B.2B (0.5%). Class Betaproteobacteria in B.2A, is primarily composed of orders Burkholderiales (3.0%), Hydrogenophilales (28.9%), Methylophilales (3.2%), and Rhodocyclales (12.1%) (Fig. 3b). The first order in turn is comprised of a single family Comamonadaceae whose members are
3. Results and discussion 3.1. Geochemical properties and bacterial load The coalmine samples used in this study have near neutral pH with highest value of 7.7 recorded in the previously exposed soil, B.2A, followed by the surface soil, B.S (6.5), and two meters below, B.2B (6.1) (Table 1), suggesting the coalmine to be a circum-neutral in nature. However, those from greater depths have slightly acidic pH with values as low as 4.7 in B.8B (Table S1). Organic carbon (0.03–2.66%), and available nitrogen (0.0001–0.0034%), was very low in all samples particularly in those beneath 2 m (Table 1, and S1). Total heterotrophic microbial load was low in general, with maximum count in B.2A (3.05 × 107 cfu g−1 soil) followed by the surface and then the underground soil profiles. Even among the underground samples, B.4B, B.6B and B.8B have exceptionally low microbial load of 5.97 × 105, 9.67 × 104, and 7.6 × 104 cfu g−1 soil respectively (Fig. S2). In fact, we could not reproducibly extract sufficient amount of metagenomic DNA from these three samples. Thus, B.2A, B.S, and B.2B with slightly higher values for the above measured parameters (Table S1; Fig. S2) were used for detailed physicochemical and microbial population analysis. The mine soil, particularly the exposed layers have huge deposit of heavy metals such as iron, lead and chromium (Table 1). Content of anions like chloride, sulfate and nitrate was highest at B·S. Non-parametric Spearman correlation analyses show that pH is negatively correlated to OC, AN, chloride and sulfate concentrations, whereas it is positively correlated to the remaining parameters (Fig. S1). One distinctive finding is high sulfate content of 143,–345 and 196 ppm in B.2A, B.S and B.2B although the pH was circum-neutral (6.1–7.7) (Table 1). Previous studies suggest that presence of carbonates, bicarbonates and chlorides of sodium, calcium and magnesium could result in pH neutralization (Pereira et al., 2014). 3
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Fig. 3. (a) Relative abundance (≥1% abundance) of phyla in Bera Colliery soil samples. Proteobacteria has been resolved up to class level and represented by similar pattern style. Complete list of phyla with their relative abundance is provided in Table S2. (b) Heatmap showing relative abundance of proteobacterial orders and identified genera.
Aphaproteobacteria, on the contrary, was present in low numbers in B.2A (15.2%) and B.S (18.2%), but was abundant in B.2B (60.3%) (Fig. 3). The class, in B.2B is comprised entirely of the order Rhizobiales (Fig. 3b). Gammaproteobacterial abundance also have a similar trend with lowest representation in B.2A (12.7%), and highest in B.2B (36.7%). Lower down the hierarchy, Enterobacteriaceaea family constituted 34% of the population in B.2B. Members of this family are known to be facultative anaerobes with many recognized for their bioremediation applications (Octavia and Lan, 2014). There is an abundance of haloalkaliphilic population in B.2A sample, belonging to the alphaproteobacterial order Rhodobacterales, and gammaproteobacterial orders Chromatiales (Halorhodospira, 6.3%) and Oceanospirillales (Halomonas, 1.6%). This may be correlated to high concentrations of sodium and chloride ions in the soil (Table 1). Actinobacteria, which is the second most abundant phylum in B.S (45%) (Table S2), warrants a special mention. It include Dietziaceae, with a single identified genus Dietzia, (Fig. S5), which is known for its chemoorganotrophic metabolism (DeLong et al., 2014). Other
oligotrophs, metabolizing complex organic pollutants (Willems, 2014). Hydrogenophilales is represented by the sole family Hydrogenophilaceae with only Thiobacillus being identified up to genus level. The genus is renowned for its facultative anaerobic and sulfur chemolithoautotrophic attributes (Orlygsson and Kristjansson, 2014; Robertson and Kuenen, 2006). Methylophilales members are obligate or facultative methylotrophs, which can utilize methanol or methylamine (but not methane) as sole source of carbon and energy (Doronina et al., 2014). Only two genera, Azoarcus (1.7%) and Zoogloea (10.3%) were identified in this order. These genera are chemoorganoheterotrophic and can degrade organic and aromatic compounds (Oren, 2014). Due to long history of underground fire in Jharia coalmines, incomplete combustion of coal might have released these hydrocarbons, as reported earlier (Melody and Johnston, 2015). High proportion of a variety of heterotrophic bacterial population of Betaproteobacteria in B.2A corroborated well to the highest availability of OC in this layer and thus suggests natural succession being initiated in the previously exposed soil surfaces. 4
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Acknowledgement Funding received from Council of Scientific and Industrial Research (CSIR), India [No. 38(1410)/15/EMR-II] and West Bengal Department of Science and Technology (WB-DST), India [No. ST/P/S&T/5G-18/ 2017] have helped to carry out the research. Sohini Banerjee and Srikanta Pal are thankful to CSIR for their fellowships. We would like to thank the editor and reviewers for their suggestions that greatly improved the quality of the paper. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.apsoil.2020.103544.
Fig. 4. Canonical correspondence analysis (CCA) ordination plot of bacterial communities (≥1% abundance) in the soil samples of Bera Colliery (large open dots representing B.2A, B.S, and B·2B) and environmental factors affecting bacterial distribution (small filled dots). The direction and length of the arrows indicate the degree and strength of correlation. The first two axes of CCA plot could explain ≥99% of total variation. OC and AN represents organic carbon and available nitrogen respectively.
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identified families with similar metabolism include Intrasporangiaceae, Nocarediodaceae, and Micrococcaceae The aerobic to microaerophilic modes of respiration in these groups (DeLong et al., 2014), might be the reason for their absence in B.2B; and in B.2A, they are possibly replaced by more specialized betaproteobacterial members. Canonical correlation analysis (CCA) performed at the phylum level showed clear segregation of microbial population among samples based on the pH, OC, and AN content of soil (Fig. 4). This indicates that distribution of population in different soil depths is dependent on geochemical parameters. In particular, the effect of pH and SO4− ion concentrations on proteobacterial population is prominent with Betaproteobacteria located on a quadrate opposite to that of Alpha- and Gammaproteobactera. 4. Conclusion Both culture independent and dependent methods used to estimate microbial population indicate that microbial densities as well as diversity are three to five-fold higher at the excavated surface of a coalmine, as compared to the soil dig out from a depth of 2 m. The observed variations in population structure corroborates well with the geochemical parameters in the respective soil. Particular mention must be made of the abundance of chemoheterotrophic betaproteobacterial members with diverse metabolic capabilities in the exposed surface resulted from previous mining operations. The geochemical properties also favor this exposed surface to be comparatively better in terms of organic carbon content, which in turn implies natural succession being in progress. Only specialized microbial populations are known to adapt to the nutritionally poor underground environments. Detailed analyses of these specialized microbial groups, particularly the anaerobic ones either by culture-based screening for members of different functional groups, or using molecular tools would provide more meaningful understanding of the ecology operative in deep-soil of active coalmines. Presence of members of Rhizobiales, Enterobacteriales and Agrobacterium in underground samples also needs further confirmation and their function therein elucidated. Thus, the present study is believed to bring new insights into the microbiology of surface and sub-surface soil of active coalmines and better our understanding of its diversity observed in relation with the geochemical properties of the soil. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 5
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profiles over 120, 000 years of ecosystem development. Front. Microbiol. 8. Walkley, A., 1947. A critical examination of a rapid method for determining organic carbon in soils-effect of variations in digestion conditions and of inorganic soil constituents. Soil Sci. 63, 251–264. Willems, A., 2014. The family Comamonadaceae. In: The Prokaryotes: Alphaproteobacteria and Betaproteobacteria, pp. 777–851.
Shen, C., Ni, Y., Liang, W., Wang, J., Chu, H., 2015. Distinct soil bacterial communities along a small-scale elevational gradient in alpine tundra. Front. Microbiol. 6, 582. Silva, L.F.O., Wollenschlager, M., Oliveira, M.L.S., 2011. A preliminary study of coal mining drainage and environmental health in the Santa Catarina region, Brazil. Environ. Geochem. Health 33, 55–65. Turner, S., Mikutta, R., Meyer-Stüve, S., Guggenberger, G., Schaarschmidt, F., Lazar, C.S., Dohrmann, R., Schippers, A., 2017. Microbial community dynamics in soil depth
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Contents lists available at ScienceDirect
Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil
Short communication
Poor nutrient availability in opencast coalmine influences microbial community composition and diversity in exposed and underground soil profiles Sohini Banerjeea,b,1, Arijit Misraa, Abhijit Sara, Srikanta Pala, Shibani Chaudhuryb, Bomba Dama,
T
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a
Microbiology Laboratory, Department of Botany (DST-FIST & UGC-DRS Funded), Institute of Science, Visva-Bharati (A Central University), Santiniketan, West Bengal 731235, India b Department of Environmental Studies, Institute of Science, Visva-Bharati (A Central University), Santiniketan, West Bengal 731235, India
A R T I C LE I N FO
A B S T R A C T
Keywords: Opencast coalmine Physicochemical properties Microbial population Vertical soil sampling Proteobacteria
Microbial community composition and geochemical properties in opencast mines in general, and particularly along depth is poorly understood. Here, we attempt to understand the change in these features in an active opencast coalmine in Bera, Jharkhand, India, using soil from the surface of an excavated coalmine; four samples from 2, 4, 6 and 8 m below the surface layer, and an exposed surface two meters above the soil. The previously exposed, surface, and two meters below samples have circum-neutral pH (7.7, 6.5 and 6.1 respectively), but it drops to 4.7 in the 8-m underground sample. Soil is nutritionally poor with low total organic carbon (0.03–2.66%), available nitrogen (0.0001–0.0034%), and heterotrophic microbial load (7.6 × 104–3.1 × 107) having lowest values in samples beyond two meters' depth. Amplicon sequences of the V1-V2 hyper-variable region of 16S rRNA gene of the previously exposed, surface, and two meters below samples show a low microbial diversity with 313, 275 and 118 operational taxonomic units respectively. Proteobacteria was the predominant phyla across all samples (97.44%–52.09%) with betaproteobacterial members such as Hydrogenophilales and Rhodocyclales being abundant in previously exposed soil (65.5%), but with negligible representation (0.5%–1.9%) in the other two. Distribution of Alphaproteobacterial and Gammaproteobacterial members was in reverse order. Thus, the study describes how poor nutrient availability in opencast coalmine influences microbial community composition and diversity in exposed and underground soil profiles.
1. Introduction Coal mining is a destructive operation which leads to deforestation, dust and noise pollution, land subsidence, erosion, accumulation of overburden dumps, and contamination of water bodies. Mine soil quality is site specific and differs from one another due to geology of the site, climatic factors and differences in mining techniques. Opencast mining has two-fold detrimental effect, first when the topsoil at miningsite is removed, and second when the overburden dumps are deposited in unmined areas leading to poor soil quality and loss of biodiversity on temporal and spatial scales (Masto et al., 2011; Saini et al., 2016). Coal mining is also one of the largest reasons for heavy metal pollution (Masto et al., 2011; Silva et al., 2011). To assess mine soil health, several parameters related to their physical, chemical, and biological properties have been used as indicators and these information have helped to develop reclamation strategies of both active and abandoned
mines around the world (Das and Chakrapani, 2011; Pasayat and Patel, 2015). Among living systems, microorganisms are preferred as indicators as they contribute in every biogeochemical cycle (Nielsen et al., 2002). Soil microbial communities may vary even by millimeters, both horizontally and vertically, depending on abiotic factors like pH, organic carbon, available nitrogen, moisture content, salinity, and its texture (Armitage et al., 2012; O'Brien et al., 2016; Shen et al., 2015). They have also been advocated to be suitable in remediation processes of contaminated soil and water. Bacterial diversity and its role in soil health is predominantly studied near the topsoil (~15 cm depth), with those at deeper soil horizons being sparsely studied because of the low biomass densities and metabolic activities (Ghiorse and Wilson, 1988). Although exponential decrease in microbial cell count with depth has been reported, some active cells do remain in deeper soil horizons that are adapted to limited nutrients and energy (Hartmann et al., 2009;
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Corresponding author. E-mail address: [email protected] (B. Dam). 1 Present Address: Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine, Houston, Texas, USA. https://doi.org/10.1016/j.apsoil.2020.103544 Received 22 September 2019; Received in revised form 25 January 2020; Accepted 5 February 2020 0929-1393/ © 2020 Published by Elsevier B.V.
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total nitrogen (TN) was measured using Kjeltek method (FOSS, Denmark) (Bremner, 1960). Organic carbon (OC) was estimated by Walkley-Black titration method (Walkley, 1947). Ion-exchange chromatography (Metrohm Basic IC plus 783) was used to assess the presence of water-soluble anions (SO42−, NO3−, NO2−, Cl−, Br−, F−, PO4−2). Elemental analyses were carried out using Atomic Absorption Spectroscopy facility at Bose Institute, Kolkata, India (iCE 3000 Series, Thermo Fisher Scientific, USA). Heavy metals (Ca, Mg, As, Cd, Co, Cr, Fe, Ni and Pb) were estimated from ~0.2 g soil sample after tri-acid (HF–HNO3–HClO4) digestion (EPA, 1996). Flame Photometer was used to measure Na+ and K+ (Jackson et al., 1976). A Spearman correlation analysis was performed using log-normalized values in GraphPad Prism-7.0.
Turner et al., 2017). Even in open cast coalmines which involve digging deep underground, ecological studies performed have mostly focused on the microbial diversity of either stockpiles or reclaimed land. Thus, objective of the present study was to understand relationship between geochemical properties and microbial distributions in exposed and underground soil profiles of an active excavated coalmine, Bera in Jharia, Jharkhand, which is one of the oldest and largest coal producing mines in India, but is not explored in term of its microbial diversity and richness. 2. Materials and methods 2.1. Site description and sampling
2.3. Microbial enumeration
Bera Colliery (23° 45′ 56″ N, 86° 25′ 44.7″ E), in the eastern flank of Jharia coalfield, is an active opencast mine that started operations in early nineteenth century (Gee, 1940). Soil samples were collected in April 2013, from different horizons of the excavated coalmine. This includes the surface layer as on the date of sampling; a coal seam two meters above surface from the wall that was exposed due to previous mining operation almost one year ago; and eight meters below the surface layer at depths of 2 m intervals (Fig. 1). Samples were named accordingly as B.2A, B.S, B.2B, B.4B, B.6B and B.8B with, ‘B’ in prefix standing for Bera, ‘S’ for the surface layer, and numbers for meters above ‘A’ or below ‘B’ the surface in suffix. For this, a core drilling rig hydraulic machine generally used by the coal miners to estimate the next layer of coal seam was used and its tip was thoroughly cleaned with 70% alcohol after every drilling. Samples were collected aseptically in sterile 50 mL falcon tubes and brought to the laboratory on ice and stored at 4 °C (for culture-based work) or −20°C (for DNA isolation) until further use.
Viable aerobic bacterial load was enumerated by plate count using 0.1 mL of the appropriately diluted samples (in saline water, 0.9% NaCl) on Luria-Bertani agar plates followed by incubation at 30 °C for 48 h.
2.4. DNA extraction, sequencing and analysis Total soil DNA was extracted from 0.5 g sample using the Fast DNA SPIN Kit for Soil (MP Biomedicals, Santa Ana, CA, USA), according to manufacturer's instructions. The V1-V2 hyper-variable region of 16S rRNA gene was amplified from the metagenomic DNA using appropriately bar-coded and adaptor ligated forward (5′-AGAGTTTGATCITGGCTCAG-3′) and reverse (5′-CTGCTGCCTCCCGTAGG-3′) primers following standardized protocol (Banerjee et al., 2018). Amplicon libraries were sequenced at Genotypic Inc., Bangalore, India on Ion PGM 318 Chip using 400 bp chemistry (Life Technologies, USA). Sequences were analyzed using the standalone installation of QIIME1 (Caporaso et al., 2010) and USEARCH (Edgar, 2010) on Biolinux following our lab's standardized pipeline (Banerjee et al., 2018). QIIME was used to estimate alpha and beta diversity (Lozupone and Knight, 2005) and was visualized using Principal Coordinate Analysis (PCoA) plot. Statistical analyses were performed on R 3.2.1 (cran.rproject.org), and figures generated using GraphPad Prism 7.
2.2. Geochemical analyses pH was measured at a 1:2.5 (wt/vol) sample-to-distilled-water ratio at 25 °C using a portable multi-parameter instrument (Hanna Instruments, USA). For all geochemical analyses, samples were dried at 105 °C overnight and thoroughly grated using a mortar and pestle before passing through a 200-mesh sieve. Available nitrogen (AN), and
Fig. 1. Sampling site. Bera coalmine, located in Jharkhand state of India. Samples are labelled as, B.S for surface layer as on the date of sampling (April 2013); B.2A is the soil scraped from two meters above surface from the wall, exposed due to previous mining operation; and B.2B represents soil drilled out from 2 m below the surface layer. A core drilling rig hydraulic machine generally used by the coal miners to estimate the next layer of coal seam was used. 2
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Table 1 Soil physicochemical properties of B.2A, B.S, and B.2B. Organic carbon (OC), available nitrogen (AN), and total nitrogen (TN) are expressed in percentage. All other values except pH are expressed in ppm.
pH OC AN TN F− Cl− Br− NO32− SO42− Na+ K+ Ca2+ Mg2+ Fe2+ Pb2+ Cr3+
B.2A
B.S
B.2B
7.71 1.17 0.0025 0.76 1.87 715.86 4.12 360.7 143.43 1445.40 9074.57 5395.93 6065.30 4547.13 665.10 713.00
6.54 2.66 0.0034 0.14 1.02 28,310.21 BDL 656.44 345.44 1242.47 8124.33 3855.93 5313.00 2595.40 162.77 519.67
6.1 1.88 0.00028 0.13 4.21 11,210.87 8.41 15.99 196.16 1350.73 7957.50 4521.40 5286.53 1476.23 161.10 367.83
BDL = below detection level.
2.5. Data deposition Raw sequence reads were deposited in fastq format to the National Center for Biotechnology Information Sequence Read Archive under BioProject accession number PRJNA491301. The project includes seven BioSamples, from two coalfields of Jharia (India), four from Tasra Colliery (not used in this study), and three from Bera Colliery (SAMN10069354, SAMN10069355, SAMN10069356) used in this study.
Fig. 2. (a) Sequence read statistics and diversity indices. (b) Venn diagram showing shared and unique OTUs in different samples of Bera Colliery. Numbers in brackets show the percent overlap.
3.2. Microbial diversity along soil depth To get a clear representation of the microbial taxa, amplicon sequencing of the V1-V2 hyper-variable region of 16S rRNA gene was performed and a total of 716,960 raw sequences were generated for the three soil samples. After pre-processing, 485,085 filtered sequences with Phred quality score of Q25, and average length of 200–350 bp was used for downstream analyses (Fig. 2a). None of the obtained sequences corresponds to OTUs of Archaea or Eukarya. Although a high sampling coverage (~99%) was obtained (Fig. S3), the number of OTUs was low in general, with highest value of 313 in B.2A followed by 275 in B.S, and a mere 118 in B.2B. Alpha diversity was also highest for B.2A as implied by the higher values of Chao1 (Fig. S4), and Shannon and Simpson indices (Fig. 2a). Venn-diagram using shared and unique OTUs shows that B.2A has almost 4.5 times the number of unique species as compared to B.2B (Fig. 2b). Uniqueness of the microbial composition in B.2B is also evident from the very few shared OTUs with B.2A (3.4%) and none with B.S (0%). The OTUs across all samples were represented by eleven distinct phyla (Table S2) with only five being in the top 1%. Percentage of unassigned OTUs was quite low (≤2%). Some assemblages of yet-to-be cultivated members, like OP11, TM7, and WPS-2 were also identified. Proteobacterial members were most predominant across all samples with highest representation in B.2B (97.44%), followed by B.2A (90.57%) and B.S (52.09) (Fig. 3a). Interestingly, in B.S, Actinobacteria comprises about 45% of the total population. Other phyla like Bacteroidetes, Chloroflexi and [Thermi] are in minor representations (≤1%) (Table S2). Distribution of proteobacterial members have an interesting trend, with Betaproteobacteria being the dominant class (65.5%) in B.2A, but with negligible representation in B.S (1.9%), and further more in B.2B (0.5%). Class Betaproteobacteria in B.2A, is primarily composed of orders Burkholderiales (3.0%), Hydrogenophilales (28.9%), Methylophilales (3.2%), and Rhodocyclales (12.1%) (Fig. 3b). The first order in turn is comprised of a single family Comamonadaceae whose members are
3. Results and discussion 3.1. Geochemical properties and bacterial load The coalmine samples used in this study have near neutral pH with highest value of 7.7 recorded in the previously exposed soil, B.2A, followed by the surface soil, B.S (6.5), and two meters below, B.2B (6.1) (Table 1), suggesting the coalmine to be a circum-neutral in nature. However, those from greater depths have slightly acidic pH with values as low as 4.7 in B.8B (Table S1). Organic carbon (0.03–2.66%), and available nitrogen (0.0001–0.0034%), was very low in all samples particularly in those beneath 2 m (Table 1, and S1). Total heterotrophic microbial load was low in general, with maximum count in B.2A (3.05 × 107 cfu g−1 soil) followed by the surface and then the underground soil profiles. Even among the underground samples, B.4B, B.6B and B.8B have exceptionally low microbial load of 5.97 × 105, 9.67 × 104, and 7.6 × 104 cfu g−1 soil respectively (Fig. S2). In fact, we could not reproducibly extract sufficient amount of metagenomic DNA from these three samples. Thus, B.2A, B.S, and B.2B with slightly higher values for the above measured parameters (Table S1; Fig. S2) were used for detailed physicochemical and microbial population analysis. The mine soil, particularly the exposed layers have huge deposit of heavy metals such as iron, lead and chromium (Table 1). Content of anions like chloride, sulfate and nitrate was highest at B·S. Non-parametric Spearman correlation analyses show that pH is negatively correlated to OC, AN, chloride and sulfate concentrations, whereas it is positively correlated to the remaining parameters (Fig. S1). One distinctive finding is high sulfate content of 143,–345 and 196 ppm in B.2A, B.S and B.2B although the pH was circum-neutral (6.1–7.7) (Table 1). Previous studies suggest that presence of carbonates, bicarbonates and chlorides of sodium, calcium and magnesium could result in pH neutralization (Pereira et al., 2014). 3
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Fig. 3. (a) Relative abundance (≥1% abundance) of phyla in Bera Colliery soil samples. Proteobacteria has been resolved up to class level and represented by similar pattern style. Complete list of phyla with their relative abundance is provided in Table S2. (b) Heatmap showing relative abundance of proteobacterial orders and identified genera.
Aphaproteobacteria, on the contrary, was present in low numbers in B.2A (15.2%) and B.S (18.2%), but was abundant in B.2B (60.3%) (Fig. 3). The class, in B.2B is comprised entirely of the order Rhizobiales (Fig. 3b). Gammaproteobacterial abundance also have a similar trend with lowest representation in B.2A (12.7%), and highest in B.2B (36.7%). Lower down the hierarchy, Enterobacteriaceaea family constituted 34% of the population in B.2B. Members of this family are known to be facultative anaerobes with many recognized for their bioremediation applications (Octavia and Lan, 2014). There is an abundance of haloalkaliphilic population in B.2A sample, belonging to the alphaproteobacterial order Rhodobacterales, and gammaproteobacterial orders Chromatiales (Halorhodospira, 6.3%) and Oceanospirillales (Halomonas, 1.6%). This may be correlated to high concentrations of sodium and chloride ions in the soil (Table 1). Actinobacteria, which is the second most abundant phylum in B.S (45%) (Table S2), warrants a special mention. It include Dietziaceae, with a single identified genus Dietzia, (Fig. S5), which is known for its chemoorganotrophic metabolism (DeLong et al., 2014). Other
oligotrophs, metabolizing complex organic pollutants (Willems, 2014). Hydrogenophilales is represented by the sole family Hydrogenophilaceae with only Thiobacillus being identified up to genus level. The genus is renowned for its facultative anaerobic and sulfur chemolithoautotrophic attributes (Orlygsson and Kristjansson, 2014; Robertson and Kuenen, 2006). Methylophilales members are obligate or facultative methylotrophs, which can utilize methanol or methylamine (but not methane) as sole source of carbon and energy (Doronina et al., 2014). Only two genera, Azoarcus (1.7%) and Zoogloea (10.3%) were identified in this order. These genera are chemoorganoheterotrophic and can degrade organic and aromatic compounds (Oren, 2014). Due to long history of underground fire in Jharia coalmines, incomplete combustion of coal might have released these hydrocarbons, as reported earlier (Melody and Johnston, 2015). High proportion of a variety of heterotrophic bacterial population of Betaproteobacteria in B.2A corroborated well to the highest availability of OC in this layer and thus suggests natural succession being initiated in the previously exposed soil surfaces. 4
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Acknowledgement Funding received from Council of Scientific and Industrial Research (CSIR), India [No. 38(1410)/15/EMR-II] and West Bengal Department of Science and Technology (WB-DST), India [No. ST/P/S&T/5G-18/ 2017] have helped to carry out the research. Sohini Banerjee and Srikanta Pal are thankful to CSIR for their fellowships. We would like to thank the editor and reviewers for their suggestions that greatly improved the quality of the paper. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.apsoil.2020.103544.
Fig. 4. Canonical correspondence analysis (CCA) ordination plot of bacterial communities (≥1% abundance) in the soil samples of Bera Colliery (large open dots representing B.2A, B.S, and B·2B) and environmental factors affecting bacterial distribution (small filled dots). The direction and length of the arrows indicate the degree and strength of correlation. The first two axes of CCA plot could explain ≥99% of total variation. OC and AN represents organic carbon and available nitrogen respectively.
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identified families with similar metabolism include Intrasporangiaceae, Nocarediodaceae, and Micrococcaceae The aerobic to microaerophilic modes of respiration in these groups (DeLong et al., 2014), might be the reason for their absence in B.2B; and in B.2A, they are possibly replaced by more specialized betaproteobacterial members. Canonical correlation analysis (CCA) performed at the phylum level showed clear segregation of microbial population among samples based on the pH, OC, and AN content of soil (Fig. 4). This indicates that distribution of population in different soil depths is dependent on geochemical parameters. In particular, the effect of pH and SO4− ion concentrations on proteobacterial population is prominent with Betaproteobacteria located on a quadrate opposite to that of Alpha- and Gammaproteobactera. 4. Conclusion Both culture independent and dependent methods used to estimate microbial population indicate that microbial densities as well as diversity are three to five-fold higher at the excavated surface of a coalmine, as compared to the soil dig out from a depth of 2 m. The observed variations in population structure corroborates well with the geochemical parameters in the respective soil. Particular mention must be made of the abundance of chemoheterotrophic betaproteobacterial members with diverse metabolic capabilities in the exposed surface resulted from previous mining operations. The geochemical properties also favor this exposed surface to be comparatively better in terms of organic carbon content, which in turn implies natural succession being in progress. Only specialized microbial populations are known to adapt to the nutritionally poor underground environments. Detailed analyses of these specialized microbial groups, particularly the anaerobic ones either by culture-based screening for members of different functional groups, or using molecular tools would provide more meaningful understanding of the ecology operative in deep-soil of active coalmines. Presence of members of Rhizobiales, Enterobacteriales and Agrobacterium in underground samples also needs further confirmation and their function therein elucidated. Thus, the present study is believed to bring new insights into the microbiology of surface and sub-surface soil of active coalmines and better our understanding of its diversity observed in relation with the geochemical properties of the soil. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 5
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