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Bacterial survival strategies in an alkaline tailing site and the physiological mechanisms of dominant phylotypes as revealed by metagenomic analyses Weimin Sun, Enzong Xiao, Max Häggblom, Valdis Krumins, Yiran Dong, Xiaoxu Sun, Fangbai Li, Qi Wang, Baoqin Li, and Bei Yan Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b03853 • Publication Date (Web): 22 Oct 2018 Downloaded from http://pubs.acs.org on October 23, 2018
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Bacterial survival strategies in an alkaline tailing site and the physiological mechanisms of
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dominant phylotypes as revealed by metagenomic analyses
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Weimin Sun1*†, Enzong Xiao2†, Max Häggblom3, Valdis Krumins4, Yiran Dong5, Xiaoxu Sun1, Fangbai Li1, Qi
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Wang1, Baoqin Li1, Bei Yan1
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1. Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management,
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Guangdong Institute of Eco-environmental Science & Technology, Guangzhou 510650, China
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2. Key Laboratory of Water Quality and Conservation in the Pearl River Delta, Ministry of Education, School of Environmental Science and Engineering, Guangzhou University, Guangzhou 510006, China 3. Department of Biochemistry and Microbiology, Rutgers University, New Brunswick NJ 08901, USA
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4. Department of Environmental Sciences, Rutgers University, New Brunswick, NJ 08901, USA
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5. Institute for Genomic Biology, University of Illinois, Urbana-Champaign, Urbana IL 61801, USA
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*Correspondence to:
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Dr. Weimin Sun
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808 Tianyuan Road, Guangzhou, Guangdong, China. Phone: 86-020- 87024633. Fax: 86-020-87024123. E-mail:
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[email protected] 17
†These authors contributed equally to this work.
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Abstract
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Microorganisms inhabiting mine tailings require specific metabolic strategies to survive, which may hold the
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potential to clean up the pollution. Effective in situ bioremediation will rely on an in-depth understanding of the
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function of the bacterial communities, especially the abundant and metabolically active phylotypes. In this study,
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the bacterial communities collected from an alkaline tailing site were profiled by 16S rRNA gene amplicon
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sequencing as well as shotgun metagenomic analysis. Our results indicated that potential for carbon and nitrogen
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fixation as well as metal resistance and transformation were widespread among the bacterial community members,
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especially in highly enriched phylotypes, such as members of Thiobacillus and Meiothermus. Important functional
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microbial guilds including carbon and nitrogen fixers may contribute to phytoremediation by providing nutrients
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for hyperaccumulator plants. In addition, metal-metabolizing bacteria may influence metal speciation and
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solubility. This discovery provides an understanding for microbial survival strategies in the tailings and lays the
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foundation for future potential manipulation of the tailing microbiome for in situ bioremediation.
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Key words: Metal-microbe interactions; Random Forest; Shotgun metagenomics; Binning; Meiothermus
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Introduction
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Mine tailings generated by disposal of mining waste usually result in adverse metal-rich environments for
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microbial growth
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microbial functions 5-7. In addition to metal(loid) toxicity, mine tailings are typically nutrient-poor, making them
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relatively inhospitable for both plants and microorganisms 8. Despite the high toxicity and low nutrient availability,
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several studies have reported that diverse microbial communities were present in these ecosystems and played
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important ecological roles in tailing environments 9-11. For example, microorganisms develop a range of survival
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strategies to mitigate the toxic damage caused by metal(loid)s. Some of these strategies can influence the transport
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and fate of metal(loid)s by affecting their speciation and solubility and thus may either increase or decrease the
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toxicity of metal(loid)s in the environment
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determine the rate of release of metals and sulfur to the environment 15. Numerous bacteria and archaea isolated
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from mining area have been shown to have important roles in generating mine drainage
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cycling of Fe and S
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contributed to nutrient accumulation in these extreme environments 18, 19. Additionally, recent “omics” techniques
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indicated that carbon and nitrogen fixation and sulfur oxidation was adapted by microorganisms inhabiting
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lead/zinc mine tailings
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primarily autotrophic metabolism as well as metal resistance 21, providing additional evidence of unique microbial
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survival strategies in mine tailing environments.
1, 2.
Exposure to these can decrease microbial diversity and biomass
17.
12-14.
3, 4
and impair specific
Several studies indicate that microorganisms may ultimately
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and impacting the
Isolation and detection of nitrogen fixing bacteria from tailings suggested that they
20.
In another study, the microbiome of an acid mine drainage was shown to exhibit a
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The acid mine tailings produced from oxidation of sulfide-bearing minerals are global environmental problems
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and have been well-studied with various reviews focusing on the microbiology
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bioremediation strategies 24. Although sharing similar characteristics with acidic mine tailings (e.g., metal-rich,
15, 22,
geochemistry
23,
and
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nutrient-poor and rapid weathering processes), alkaline tailings have been relatively less studied. In comparison
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to acidic mine tailings, the mineralogy of alkaline tailings generally provides more suitable geochemical
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conditions for soil development, which subsequently enables the revegetation of the tailings and establishment of
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more stable and sustainable habitat
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accelerating the soil development in alkaline tailings via promoting mineral precipitation and nutrient
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accumulation
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tailings, however, has not been specifically addressed. Such information may provide an attractive direction for
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directing the management of contaminated tailing sites, especially for alkaline tailings. Through the use of the
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recent omics-related techniques, it is possible to track the metabolic potential of the indigenous microbial
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community. In addition, the development of statistical tools, such as the ensemble model, provides a means to
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study the environment-microbe interactions derived from high throughput sequencing data 26, 27.
25.
25.
Microbial activities are thought to play important ecological roles by
An in-depth understanding of the metabolic capabilities of the innate microbiota in alkaline
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In this study, we selected an alkaline tailing site which received tailings from Sb mining fifteen years ago but has
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since received tailings from Pb/Zn mining. The shift of tailing sources created a metal gradient along the path of
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the tailing flow and a deficiency in nutrients in the whole tailing site. Therefore, the study site is an excellent
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natural habitat to study the microbial survival and evolution strategies in response to these two perturbations:
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metal(loid)s contamination and nutrient limitation in alkaline tailings. Here, geochemical analyses, 16S rRNA
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gene sequencing, statistical analyses, and metagenomic binning were coupled to reveal the microbial survival
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strategies. The overall goals of this study are to understand: (i) the bacterial diversity and community inhabiting
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the alkaline tailing site and (ii) the metabolic potentials of the indigenous microbiota, with a focus on the dominant
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phylotypes.
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Materials and Methods
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Soil sampling
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The study site was located in a Pb-Zn and Sb tailing site in Nandan County, Guangxi, China (Figure S1). The
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tailing site was geographically divided into three zones (Zones I, II and III). The GPS coordinates were as follows:
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Zone I: 24.852086°N, 107.672283°E; Zone II: 24.852089°N,107.672286°E; and Zone III: 24.852086°N,
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107.672286°E. A total of 34 tailing samples for both geochemical and molecular analyses (designated CSWK01-
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34) were taken from the upper 20 cm of the sediments using a sterile soil sampler (Table S1). The samples were
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cooled to 3-4 °C immediately after sampling for shipment to the laboratory, where they were then stored at -80 °C
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until analysis. The geochemical analyses of environmental parameters such as pH, total C, total N, and metals
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and metalloids are provided in the supplementary information.
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Illumina MiSeq sequencing of 16S rRNA genes
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Total genomic DNA was extracted from 0.5 g of tailing samples using PowerSoil® Soil DNA Isolation kit (MO
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BIO Laboratories, Inc. Carlsbad, CA) according to the manufacture’s protocol. Amplicon sequencing was
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performed on an Illumina MiSeq platform at Ecogene (Shenzhen, China) of the V4-V5 hypervariable region of
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the 16S rRNA genes 28. Details regarding the pipeline for 16S rRNA analysis is provided in the supplementary
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information. Numerical analyses such as Random Forest (RF) ensemble model and co-occurrence network was
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used to correlate the interaction among geochemical parameters and bacterial community and diversity. The
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details to perform RF and co-occurrence network analysis were described in a previous study 26 and are briefly
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summarized in the supplementary materials.
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Metagenome sequencing and analysis 5
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Metagenomic libraries from four tailing samples (one sample each from zones I and II, and two from zone III)
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were sequenced on the Illumina Hiseq 4000 platform (paired-end 150 bp reads) at Novogene (Tianjing, China).
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Metagenomic libraries were generated using NEB Next® Ultra™ DNA Library Prep Kit for Illumina (NEB, USA)
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following the manufacturer’s protocols. A total of 88 Gb raw sequence data was generated (222,104,532 raw
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reads) from four metagenomes. Raw data were first processed by Trimmomatic 0.36 for adapter removal and
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moderate quality trimming to obtain “clean” data for subsequent data analysis as follows: raw sequence reads that
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contained a quality score less than 38 for more than 40 bp, more than 10 bp ambiguous “N”, and/or an overlap
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with the adapter in excess of 15 bp were discarded to obtain “clean” data for subsequent data analysis (Table S2
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for detailed information) 29. Metagenomes were assembled using metaSPAdes from SPAdes v3.10
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trimmed reads were mapped to the contigs using Bowtie2 version 2.2.9 31. Contigs shorter than 1kb or with an
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average coverage less than five were discarded from the assembly. The taxonomic assignment of the sequences
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was conducted using the Last Common Ancestor method with default parameters
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analysis was performed by mapping sequences to KEGG,COG and/or SEED 32, 34. Raw sequences of 16S rRNA
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and metagenomics reads have been made available in the NCBI Sequence Read Archive (SRP131706).
32, 33,
30,
and the
while the functional
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Binning of metagenomics contigs
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Contigs were binned using CONCOCT (version 0.4.0) with default settings (Table S3 for detailed information)35.
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CheckM 1.0.6 was used to assess the completeness and contamination of the recovered genome bins 36. Genome
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bins with completeness >80 % were classified as “high quality”, and were re-binned using the CONCOCT
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workflow. The resulting bins were again evaluated with CheckM. Only re-binned genome bins with completeness
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>80% were used for detailed downstream analyses. The abundance of each bin under different treatments was
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estimated by mapping the high-quality reads of individual datasets to the contigs from bins using Bowtie 2. The
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taxonomic and functional annotations for various genomic bins are provided in supplementary information. 6
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Results
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Geochemical conditions
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A number of geochemical parameters, which can be divided into nutrients for microbial growth and metal(loid)s,
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were measured within the tailing samples (Figure S2 and Table S4). All samples were alkaline (ranging from 7.7
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to 10.8) except for CSWK03 (pH: 4.4). The percentage of total N (TN), total C (TC), total H (TH), total S (TS),
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total organic carbon (TOC), and soluble S (SS) were measured as parameters essential for microbial growth.
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Among these, TC represented 2.5±1.3 % (average ± standard deviation) of the sample weight, but TOC only
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accounted for 0.4±0.8% of the sample weight. In most samples, TOC accounted for
