- Email: [email protected]
Effects of Cd, Cu, Zn and their combined action on microbial biomass and bacterial community structure
Accepted Manuscript Effects of Cd, Cu, Zn and their combined action on microbial biomass and bacterial community structure Jiuwei Song, Qunli Shen, Lu Wang, Gaoyang Qiu, Jiachun Shi, Jianming Xu, Philip C. Brookes, Xingmei Liu PII:
S0269-7491(18)32107-9
DOI:
10.1016/j.envpol.2018.09.011
Reference:
ENPO 11553
To appear in:
Environmental Pollution
Received Date: 11 May 2018 Revised Date:
15 August 2018
Accepted Date: 3 September 2018
Please cite this article as: Song, J., Shen, Q., Wang, L., Qiu, G., Shi, J., Xu, J., Brookes, P.C., Liu, X., Effects of Cd, Cu, Zn and their combined action on microbial biomass and bacterial community structure, Environmental Pollution (2018), doi: 10.1016/j.envpol.2018.09.011. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Graphic abstract
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Effects of Cd, Cu, Zn and their combined action on microbial
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biomass and bacterial community structure
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Jiuwei Song, Qunli Shen, Lu Wang, Gaoyang Qiu, Jiachun Shi, Jianming Xu,
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Philip C. Brookes, Xingmei Liu*
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Institute of Soil and Water Resources and Environmental Science, College of
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Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of
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Agricultural Resources and Environment, Zhejiang University, Hangzhou 310058, P.R.
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China
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AUTHOR INFORMATION
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Corresponding Author
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*Dr. Xingmei Liu
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College of Environmental and Natural Resource Sciences, Zhejiang University,
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Hangzhou 310058, China;
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*phone: +86-571-8898-2419; fax: +86-571-8898-2419; e-mail: [email protected].
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Abstract: Heavy metal pollution can decrease the soil microbial biomass and
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significantly alter microbial community structure. In this study, a long-term field
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experiment (5 years) and short-term laboratory experiment (40 d) were employed to
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evaluate the effects of heavy metals (Cd, Cu, Zn), and their combinations at different
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concentrations, on the soil microbial biomass and the bacterial community. The ranges
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of heavy metal concentration in the long-term and short-term experiments were
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similar, with concentration ranges of Cd, Cu and Zn of about 0.3-1.5, 100-500, and
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150-300 mg kg-1, respectively. Microbial biomass decreased with increasing soil
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heavy metal concentrations in both the long-term and short-term experiments. The
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interaction between soil physicochemical factors (pH, TN, TC) and heavy metals (Cd,
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Cu, Zn) played a major role in change in the bacterial community in long-term
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polluted soil. In the laboratory experiment, although each heavy metal had an adverse
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effect on the microbial biomass and community structure, Cu appeared to have a
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greater role in the changes compared to Cd and Zn. However, the synergistic effects
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of the heavy metals were greater than those of the single metals and the synergistic
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effect between Cu and Cd was greater than that of Cu and Zn.
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Capsule abstract: In a soil containing a combination of Cd, Cu and Zn, Cu has the
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major influence on microbial biomass and the bacterial community.
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Keywords: Heavy metals, Biomass C, ATP, Bacterial community
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1. Introduction
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There is increasing concern about soil pollution by heavy metals because of their
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toxicity to plants, animals and human beings and their lack of biodegradability. The
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anthropometric release of potentially toxic elements currently exceeds the inputs of
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heavy metals from global weathering processes, which has a significant impact on the
ACCEPTED MANUSCRIPT biosphere (Touceda-González et al., 2017). Cd, Cu, and Zn have been reported to
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decrease microbial biomass (Brookes and McGrath, 1984; Wang et al., 2007; Giller et
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al., 2009) and inhibit soil enzyme activities in heavy metal polluted soils (e.g.
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Wyszkowska et al., 2012). In soil ecosystems, microbes play important roles in
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nutrient cycling, organic matter decomposition and plant nutrient utilization (e.g.
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Stockdale and Brookes, 2006: Geisseler et al., 2010). Microbial properties, e.g. soil
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microbial biomass, diversity and activity of soil microbial communities, are
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commonly used as indicators of metal pollution, due to their high sensitivity to
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metal-induced stress (Epelde et al., 2009; Pardo et al., 2014) and rapid response to
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disturbances, their ecological relevance and ability to provide information on the
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integration of many environmental factors (Bloem et al., 2006; Garbisu et al., 2011).
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Previous studies showed that heavy metal contamination has both long-term (Lorenz
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et al., 2006; Oliveira and Pampulha, 2006) and short-term (Bouskill et al., 2010; Ding
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et al., 2017) toxicity effects on terrestrial microbial communities.
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Comparisons of the results of long-term field experiments and short-term
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laboratory studies on the toxicity of heavy metals to microbes need to be interpreted
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with caution (Giller et al., 2009). The main reason for possible difference is,
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presumably, that changes in microbial properties are the result of multiple factors,
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such as soil physicochemical properties and, most importantly, small but frequent
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inputs of toxic pollutants (Frossard et al., 2017; Zhao et al., 2016) over the long-term
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(chronic changes) compared to much larger short-term (acute changes) inputs in
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laboratory experiments. However this has still not been resolved in the two different
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experimental approaches. Soil physicochemical properties (e.g. soil organic matter,
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moisture, pH, soil type, etc.) not only influence the toxicity of heavy metals, but also
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contribute to shifts in microbial community structure (Stemmer et al., 2007; Kenarova
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et al., 2014) . Therefore, it is important to evaluate the long-term and short-term
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effects of heavy metals on microbial biomass and the microbial community in soils of
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similar physicochemical properties. In recent years, there have been many studies
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showing the shifts of bacterial community caused by heavy metals under long-term
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ACCEPTED MANUSCRIPT pollution (Chodak et al., 2013; Stefanowicz et al., 2012). For example, soil metal
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pollution significantly shifted the bacterial community composition due to As, Cd and
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Pb contamination (Li et al., 2016). Yao et al. (2017) found significant correlations
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between microbial community profiles and a combination of Co, Zn, Hg, As and Se
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concentrations in sediments. The effects of heavy metal interactions between Cd, Cu,
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and Zn on microbial enzyme activity and biomass were previously studied in
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short-term experiments (Renella et al., 2003; Sharma et al., 1999). Renella et al. (2003)
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also showed that Cu and Zn showed synergistic increases on the effects of Cd toxicity
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on the activities of acid and alkaline phosphatase and soil ATP contents. However,
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apart from a few exceptions, most of the above research was focused on the effects of
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single metals or mixtures of metals on soil microbes and much less on interactions
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between different metals. This is addressed in our research.
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High-throughput sequencing techniques, such as Illumina sequencing of 16s rRNA
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amplicons, provide an effective resolution method to study the phylogenetic
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composition of microbial communities (Caporaso et al., 2011). The V4 region, widely
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supported as a standard 16s rRNA region, has been accepted by the Earth
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Microbiology Project for general microbial community assessment in a range of very
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different environments (Gilbert et al., 2014). Redundancy analysis (RDA) and
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variation partition analysis (VPA) are increasingly employed to analyze the
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contribution of environmental factors on soil microbial communities (Chen et al.,
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2016; Liu et al., 2017). In the present study, particular emphasis is placed on the novel
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use of the above technologies in determining the effects of heavy metals and other
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environmental factors on soil bacterial communities. This is the first study that has
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compared the results of long-term field experiments and short-term laboratory studies
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on the toxicity of heavy metals on soil microbes, specifically to better understand the
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interaction between Cu, Cd and Zn.
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The main objective were to simultaneously investigate and compare the effects of
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Cd, Cu, Zn and their combined action on microbial biomass and bacterial community
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hypothesis was heavy metals have significant negative effects on microbial biomass
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and bacterial communities, and there are significant interactions between different
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metals.
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2. Materials and methods
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2.1. Soil characterization and experimental design
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2.1.1. Field Experiment
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The experimental soils were taken from the Wenling region, Zhejiang Province,
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China. Each was sampled from the surface layer (0-15 cm depth) of five different
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paddy fields (non-flooded) from Wenling, each contaminated with heavy metals.
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Random samples were taken from each field, initially to determine the concentration
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gradients of Cd (Cd1-Cd5), ranging between 0.3-1.5 mg Cd kg-1 soil. After collection,
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the soils were sieved moist < 2mm, soil moisture adjusted to 40% of water holding
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capacity (WHC) then incubated at 25 oC for 7 d prior to determination of microbial
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biomass carbon (biomass C), ATP and community structure. The heavy metal contents
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in the soils from the selected sites were determined after air drying and finely grinding
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< 100 mesh. The pH (1: 2.5 soil: water) range was 4.51-5.21, organic C 1.96-3.21%,
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total N contents 0.19-0.31% and the C/N ratios 9.39-11.27 in the soils of the five sites
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respectively. The soil was a loamy clay. Soil Cd, Cu and Zn concentrations and
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physicochemical properties in the soils of the five sites are given in Table 1 and other
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heavy metals concentrations and soil inorganic nutrients in Supplementary Table S1.
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2.1.2. Laboratory Experiment
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Three different concentrations of Cd, Cu, Zn as sulfate and their combinations were
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added to soils already contaminated with the lowest Cd content (Cd1). There were 22
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treatments, including control; 0.5, 1.0, 1.5 mg kg-1 Cd added (Cd1, Cd2, Cd3); 100,
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250, 400 mg kg-1 Cu added (Cu1, Cu2, Cu3); 150, 200, 250 mg kg-1 Zn added (Zn1,
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medium and high concentrations (the concentrations of Cd, Cu and Zn in the
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combinations were the same as those of the single heavy metals). Soil moisture was
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adjusted to 40% WHC, and 12.5 g kg-1 of corn powder (40% C；0.7% N ) and 2.86 g
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kg-1 of ammonium nitrate (N content 35%) were added to the soils to provide
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additional C and N as substrates. The soil samples (moist soil containing 500 g
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oven-dry soil) were incubated in air tight 1 L jars at 25 ℃ for 40 d in darkness. The
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jars were opened every 2 d to permit aeration, water added to adjust to constant
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weight and the soils sampled at 40 d of incubation for microbial measurements.
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2.2. Biomass C measurements
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Soil microbial biomass C was determined by the chloroform fumigation-extraction
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method (Vance et al., 1987; Wu et al., 1990). Moist soil (previously treated as above)
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containing 10 g oven dry soil was fumigated with alcohol free chloroform for 24 h at
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25 ℃ in the dark and the CHCl3 then removed with a vacuum pump. Another part of
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the soil was not fumigated and incubated under the same conditions. The soils were
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then extracted with 40 mL 0.5 M K2SO4 at 220 rpm for 30 min and filtered (Whatman
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42 filter). Finally the filtrates were adjusted to pH 2-3 with HCl, and total organic
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carbon (TOC) determined using a Total Organic Carbon Analyzer TOC-V/CPN (Multi
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N/C 2100, Germany). Microbial biomass C was calculated from: biomass C = (Cf -
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Cnf)/kEc, where Cf is total organic C extracted from fumigated soil; Cnf is total
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organic C extracted from non-fumigated soil and kEc (the proportion of biomass C
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extracted following fumigation is 0.45 (Vance et al., 1987; Wu et al., 1990).
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2.3. ATP measurements
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ATP was extracted from the soils (Jenkinson and Oades, 1979) on the same day as
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the microbial biomass C measurements. At each time, three replicates of moist soil,
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each containing 3 g oven-dry, were taken from each treatment and weighed into 50
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mL centrifuge tubes. These soils were each ultrasonified with 25 mL of extractant A
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(Redmile-Gordon et al., 2011) for 2 min. A further three soil portions of each
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treatment were ultrasonified with 25 mL of extractant B (extractant A containing
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5×10-4 M ATP). The soil suspensions were then cooled on ice for about 10 min then
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filtered through Whatman 42 filter papers. Measurement of ATP was done using a
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bioluminometer, with the fire-fly luciferin-luciferase reagent (Qiu et al., 2016).
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2.4. Heavy metal measurements
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The concentrations of total heavy metals in the soils were determined by an
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ICP-MS (inductively coupled plasma mass spectrometer). The soil was air-dried and
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sieved < 100 mesh. Soil (0.20 g) was subjected to microwave digestion with 4 mL
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concentrated HNO3 and 2 mL HF. Available soil heavy metals were also determined
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by ICP-MS following extraction of 5 g soil with 50 mL 0.01 M CaCl2 after shaking
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for 2 h at 250 rpm.
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2.5. Bacterial 16S rRNA Gene Amplification, Illumina Sequencing, and Data
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Processing
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The field soils and some short-term heavy metal contaminated soils were selected
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for DNA extraction. Total genome DNA from soils (0.5 g) was extracted using a Fast
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DNA Spin Kit (MP Biomedical, France) following the manufacturer’s instructions.
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The concentration and purity of DNA were determined on 1% agarose gels. The 16S
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rRNA genes of the V4 regions were amplified using a specific primer (515F-806R).
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The forward primer was 515F (5’-GTG CCA GCM GCC GCG GTA A-3’), and the
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reverse primer consisted of a seven bp barcode and 806R (5’-GGA CTA CHV GGG
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TWT CTA AT-3’). The purified amplicons were then sequenced on an Illumina Miseq
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sequencing platform (Illumina Inc., San Diego, CA, USA) at Novogene Co., Ltd,
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Beijing, China. Sequence analyses were carried out by Uparse software (Uparse
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v7.0.1001, http://drive5.com/uparse/) (Edgar, 2013). Sequences with ≥ 97% similarity
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were assigned to the same OTUs. Representative sequences of each OTU were
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ACCEPTED MANUSCRIPT screened for further annotation. The RDA, Mantel test results, and VPA were
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calculated from the R package vegan (Oksanen et al., 2012). The dataset of 16S rRNA
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gene sequences were deposited in NCBI’s Sequence Read Archive (SRA) with
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accession numbers SRP142650 and SRP142656 respectively.
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2.6. Data analyses
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All data were analyzed using Origin 9.0 and SPSS 20.0 software. One-way
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ANOVA was used to analyze the treatment effects. Differences with values of P <
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0.05 were considered statistically significant. All analytical data are the means of
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triplicate determinations.
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3. Results
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3.1. The relationship between ATP and biomass C in field experiment
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There was a significant linear correlation between ATP and biomass C
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concentrations in the heavy metal polluted field soils (R2 = 0.80, Fig. 1). The contents
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of ATP and biomass C decreased linearly from site 1 to site 5. Soil ATP ranged from
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2.06 to 5.00 nmol g-1 soil, and biomass C from 287.4-770.8 µg g-1 soil. The mean
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biomass ATP concentration was 5.82 µmol g-1 biomass C.
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3.2. Effects of heavy metals on biomass C in field experiment
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correlated with the power functions (Fig. 2). Total Cd had the strongest negative
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relationship with biomass C, with a correlation coefficient of 0.92 (Fig. 2a). The
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relationship between Cu and biomass C was the weakest, albeit with a statistically
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significant correlation coefficient of 0.77 (Fig. 2b). When heavy metal concentrations
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were high, the biomass C content was low, and vice versa (Fig. 2d). Because all the
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soils contained Cd, Cu and Zn, it was not possible to determine if the results were due
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to single metals or metal-metal interactions.
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3.3. Effects of soil physicochemical properties and heavy metals on bacterial
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communities in the field experiment In the field experiment, the changes in the bacterial community were clearly
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affected by heavy metals and soil physicochemical properties. The first two
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environmental factors of RDA accounted for 77.44% of the changes in the soil
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bacterial community (Fig. 3a), with RDA1 explaining 61.01% of the changes. It is
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difficult to determine which individual factors played key roles in the changes in the
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bacterial community because pH, Cd, Zn and Cu all had small angles with the RDA1
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axis. The angles between TN (total nitrogen), TC (total carbon) and the RDA2 axis
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were small, and RDA2 explained 16.43% of the changes in the soil bacterial
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community.
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VPA was used to calculate the relationships between soil physicochemical factors
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(pH, TN, TC) and the Cd, Cu and Zn contents to explain the changes in bacterial
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community structure (Fig. 3b). The total variance of 78.36% for bacteria was
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explained by the soil physicochemical factors and the amount of heavy metals, and
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their interaction explained 48.16% of the variations. The individual effects of soil
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physicochemical factors and the amount of heavy metals accounted for 15.08% and
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15.12% respectively of the variations in the bacterial community. The Mantel test
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further confirmed the correlation between these factors and the bacterial community.
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3.4. Changes of biomass C and ATP contents in heavy metal amended soil
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Different combinations of heavy metals were added to the field soil with the lowest
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Cd concentration (Cd1). After 40 d incubation, the biomass C and ATP contents were
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determined. The biomass C contents in soils with high concentrations of Cu+Zn and
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Cd+Cu+Zn decreased significantly compared to the control soil, (-22.24% and
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-34.13% respectively) (Fig. 4a). With the Cu and Zn treatments, biomass C content
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decreased with increasing heavy metal concentrations. However, it did not decrease
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significantly with increasing soil total Cd contents (Fig. 4a).
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concentrations significantly decreased by 56.1% compared to the control soil (Fig. 4b).
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With Cd+Zn, Cu+Zn, and Cd+Cu+Zn treatments, soil ATP contents also decreased
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significantly with increasing heavy metals concentrations. However, there were no
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significant differences between the ATP contents of single heavy metals (Cd, Cu, Zn
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only) between the heavy metals concentration increases. The mean biomass ATP
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concentration was 13.30 µmol ATP g-1 biomass C, and the two parameters were
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significantly correlated (p < 0.01) (Supplementary Figure S2).
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3.5. Bacterial community composition in field and laboratory experiments
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The 7 dominant phyla of bacterial community both in long-term and short-term
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contaminated soils were selected to determine the effects of heavy metals. The main
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phyla were: Proteobacteria, Actinobacteria, Acidobacteria and Chloroflexi (Fig. 5).
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Proteobacteria was the dominant phylum in both the short and long term heavy metal
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polluted soil. In the field experiment, the relative abundance of Actinobacteria
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significantly decreased with increasing heavy metal contents. In the laboratory
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experiment, the relative abundance of Proteobacteria in all treatments containing Cu
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was significantly lower than in the control soil. The relative abundance of
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Actinobacteria in the metal treated soils in the laboratory experiment were
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significantly higher than in the control and the treatment with the highest
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concentrations of heavy metals (Cd3+Cu3+Zn3), comprising 30.38% of the total
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sequences. With the exception of the Cd3 treatment, the relative abundances of
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Acidobacteria were significantly higher than in the control. The bacterial community
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composition in field site 5 and the Cd3+Cu3+Zn3 treatments were significantly
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different, although their heavy metal contents were the same.
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3.6. Relationship between heavy metals and bacterial community in the laboratory
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experiment
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In the short-term laboratory incubation experiment, changes in the bacterial
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first two environmental factors of RDA accounted for 85.26% of the changes in the
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soil bacterial community (Fig. 6a) and RDA1 explained 69.81%. The angle between
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Cu (TCu and ACu) and the RDA1 axis was the smallest, and showed a positive
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correlation with RDA1. The angles between Zn (TZn and AZn), Cd (TCd and ACd)
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and the RDA2 axis were small, and positively correlated. RDA2 explained 15.45% of
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the changes in the soil bacterial community.
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VPA was used to calculate the interactions of the three heavy metals (both total and
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available) on bacterial community changes (Fig. 6b), accounting for 65.85% of the
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changes. Cd, Cu and Zn explained 8.38%, 18.78% and 10.28% respectively while the
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slight interactions between Cd and Zn only explained 0.40% of the total variance. The
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combination of Cd, Cu and Zn did not explain changes in the bacterial community
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(-3.58%).
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4. Discussion
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4.1. The effect of heavy metals on biomass C and ATP in soil
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Brookes and McGrath, (1984) published the first report that heavy metals, at or
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around current European permitted soil heavy metal limits, decreased the size of the
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soil microbial biomass in field soils. Our study investigated the separate effects of
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long-term and short-term heavy metal contamination in both field and laboratory
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incubations. The significant negative correlations between single metals (Cd, Cu and
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Zn) and biomass C indicated that each metal separately decreased the biomass C
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concentrations in the field experiment (Fig. 2). Despite the low Cd concentrations in
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the field soil it apparently produced the most significant negative correlation with
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biomass C (Fig. 2a). However, this analysis takes no account of possible interactions
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between biomass C and synergistic effects of soil heavy metals. These results contrast
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markedly with those from the short term laboratory experiment (Fig. 4a). The
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threshold values of Cd, Cu and Zn given by the Chinese Environmental Quality
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15618-1995). In both experiments, the ranges of soil heavy metal concentrations were
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comparable. In the field experiment the maximum concentrations were 300 Zn, 500
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Cu and 1.5 mg Cd kg-1 soil, and in the laboratory experiment, 250, 400 and 1.5 mg
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kg-1 soil respectively. However, unlike in the field experiment there were no changes
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in biomass C at lower metal concentrations in the laboratory experiment. The main
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responses were marked declines in biomass C in the high Cd+Zn treatments and in the
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high Cd+Cu+Zn treatments (Fig. 4). These results indicate the need for caution when
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comparing results from chronic long-term effects of heavy metals in the field with
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those from acute short-term laboratory experiments (Giller et al., 2009). Renella et al.
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(2002) also indicated that the effects of long-term field exposure to metal toxicity
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cannot be inferred by using heavy metal salts in short-term studies, at least as far as
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impacts on the microbial biomass are concerned. However the results from the
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short-term laboratory experiment clearly indicated that interactions between metals
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produced significant decreases in biomass while single metals did not. This showed
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that there is an additive or synergistic effects between heavy metals, which is
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consistent with Sharma et al. (1999). The long-term field experiment also
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demonstrated that it is inadvisable to base heavy metal effects on the analysis of a
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single metal. For example, as discussed above, in the long-term field experiment, the
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strongest negative correlation between biomass C and heavy metals was with Cd. Yet,
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in the laboratory experiment, Cd had no significant negative effect on biomass C
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unless in combination with other metals (Fig. 4a).
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Soil ATP measurements also provide a good index of soil microbial biomass
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(Jenkinson et al., 1988; Contin et al., 2001) in both substrate amended and non
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amended soils. Following short term additions of heavy metals to soil, again only the
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combination of Cd, Cu, and Zn decreased soil ATP contents, while the other
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treatments (single heavy metal and two heavy metals combination) had no negative
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effects. This supports the above argument. Both Jenkinson et al., (1988) and Contin et
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al. (2001) compiled correlated ATP and biomass C then available in the literature and
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C, respectively. However, the concentrations of biomass ATP covered a reasonably
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wide range, from about 6 to 14 µmol g-1 biomass C (Contin et al., 2001). The average
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concentration of biomass ATP in soils contaminated by heavy metals in our field
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experiment was 5.82 µmol g-1 biomass C, which is very close to the biomass ATP
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concentration of 7.18 measured by Brookes and McGrath (1984) in heavy metal
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contaminated soils. However, the mean biomass ATP concentration was 13.30 µmol
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g-1 biomass C in the short-term laboratory experiment, which was much higher than in
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the field experiment (Fig. S2 and Fig. 1). We tentatively offer the following
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hypothesis. In contaminated soil, microbes need more energy to survive under adverse
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conditions (Mikanova, 2006). Zhang et al. (2010) also demonstrated that heavy metal
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stress enhanced the energy expenditure of microbes and increased microbial
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respiration. Microbial communities in contaminated soils would be expected to evolve
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as integrated systems adapted to local environmental gradients of anthropogenic stress
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(Hoostal et al., 2008), because genes associated with metabolic responses to
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environmentally selective agents (such as heavy metals) are usually found in plasmids
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and can be transferred laterally among distantly related taxa within microbial
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communities (Coombs and Barkay, 2004). When microbes first come into contact
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with heavy metals, it is possible that, because of their increased metabolic expenditure,
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the ATP content increases and the microbial biomass, providing an endocellular
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energy source, decreases, which would account for this discrepancy. Over time, the
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microbes apparently adapted to heavy metal stress, and the microbial community and
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the biomass ATP contribution reverted to more usual published levels. This may
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explain why the biomass ATP concentration in the short-term experiment differed
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from the long-term experiment. Further work should be done to clarify this
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phenomenon.
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4.2. The effects of heavy metals on the bacterial community
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The toxicity of heavy metals to bacterial communities is greater than to fungi
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groups (Proteobacteria, Actinobacteria, Acidobacteria and Chloroflexi) in the different
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heavy metals treatments (Fig. 5). These four dominant phyla accounted for nearly
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80% of the total bacterial abundance both in the field and laboratory experiments.
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Proteobacteria is considered to be the dominant bacteria in the heavy metal
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contaminated soil (Idris et al., 2004). There was also a significant increase in the
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relative abundance of Acidobacteria in the heavy metal contaminated soils at the
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phylum level, which is also consistent with previous studies (Li et al., 2017).
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Compared with the control, the relative abundance of Chloroflexi in all soils treated
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with Cu in the short-term experiment were significantly higher, and consistent with Li
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et al. (2015) in soils of pH 4-4.5. However, the bacterial community composition in
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site 5 and Cd3+Cu3+Zn3 treatments were significantly different, although their heavy
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metal contents were the same. Li et al. (2015) found that the bacterial communities
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changed over time in Cu contaminated agricultural soils, and the site effect is
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presumed to be the determinant factor in microbial community shifts (Macdonald et
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al., 2011).
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In the field experiment, the bacterial community was affected by pH, Cd, Zn and
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Cu contents, and TN and TC also contributed. (Fig. 3a). The shifts in bacterial
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community structure therefore depend not only on heavy metals concentrations but
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also on other factors e.g. soil organic matter, moisture, pH and soil type (Boivin et al.,
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2006; Kenarova et al., 2014). Li et al. (2017) showed that heavy metals were the most
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important factors affecting the microbial community compared with other factors (e.g.
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pH, soil C and N). Zhang et al. (2016) demonstrated that heavy metals could mask the
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effect caused by soil physicochemical properties in wetland soil. However, in
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metal-contaminated forests the structure of the soil microbial community was shown
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to be principally dependent on soil pH (Chodak et al., 2013). Similarly Jiang et al.,
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(2016) showed reported that soil pH, rather than Cu concentration, was the main
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factor affecting the bacterial community). Our results showed that 78.36% of the
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bacterial community changes could be explained by soil physicochemical factors (pH,
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ACCEPTED MANUSCRIPT TN, TC). The amount of heavy metals (Cd, Cu, Zn), and their interaction explained
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48.16% of the changes in the bacterial community (Fig. 3b). This indicates that the
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changes in the bacterial community was mainly the result of the interactions of soil
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physicochemical factors (pH, TN, TC) and heavy metals (Cd, Cu, Zn). The Mantel
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test results further confirmed that these factors were significantly related to the
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bacterial community.
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In our laboratory experiment, we used the same soil as in the field experiment and
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the soil properties hardly changed after the addition of heavy metals. Therefore we
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can directly compare the effects of heavy metals on the different bacterial
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communities. RDA1 explained 69.81% of the changes in the soil bacterial community
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following the addition of heavy metals, while the angle between total or available Cu
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was very small (Fig. 6a). All the Cu treatment data points converged, and the
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community structure was greatly affected by Cu. VPA showed that the order of the
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individual contribution rates of heavy metals to the changes in the bacterial
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community were Cu > Zn > Cd in the laboratory experiment, which contributed
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18.78%, 10.28% and 8.38% respectively (Fig. 6b). It has been previously shown that
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Cu contamination can exert a large effect on soil microbial biomass, enzyme activity,
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and soil microbial community (Li et al., 2015; Wang et al., 2007). The probable
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reason why Cu made the largest contribution is that Cu not only binds to enzyme
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molecules, but also enzyme-substrate complexes, both of which result in decreased
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enzyme activities (Huang and Shindo, 2000). High Cu concentrations may lead to the
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formation of reactive oxygen species and subsequent oxidative stress, and also to the
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oxidation of protein, DNA and lipids, resulting in cell death and changes in microbial
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community structure (Li et al., 2014). The interaction between Cd and Cu explained
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23.08% of the bacterial community while Cd and Zn explained only 0.40% (Fig. 6b).
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Our results suggested that Cu and Cd have synergistic effects on bacterial community
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changes. This is consistent with the result that the additive effect of Cu and Cd is
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significantly greater than that of Zn and Cd in affecting soil microbes (Renella et al.,
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2003). The competition of Cd and Zn for adsorption sites has been reported
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ACCEPTED MANUSCRIPT previously (Christensen, 1987). In our experiment, because the available Zn content
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was much higher than that of available Cd, Zn would dominate in the competition
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between Zn and Cd. When the three heavy metals were applied together, the
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synergistic effect between Cu and Cd was inhibited, while that between Cu and Zn
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was enhanced. The combination of the three heavy metals caused little change to the
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bacterial community (-3.58%). The change was mainly a result of the toxicity of
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single heavy metal and the synergistic effects between Cd-Cu and Cu-Zn.
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5. Conclusions
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The long-term effects of heavy metals on microbes in the environment cannot be
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duplicated in short-term laboratory experiments. The interactions between soil
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physicochemical factors (pH, TN, TC) and heavy metals (Cd, Cu, Zn) play a major
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role in changes in the bacterial community in long-term polluted soil. At the heavy
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metals concentration applied in the laboratory experiment, the effects of Cu on the
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microbial biomass and bacterial community were greater than Cd and Zn. Although
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Cd had no significant effect on the microbial biomass below 1.5 mg kg-1, the
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synergistic effect between Cd and Cu made a significant difference to the bacterial
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community. There was also a competitive relationship between Cd and Zn. Therefore,
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should heavy metal standards be applied in the future for soil microbes, these results
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suggest that it is important that the combined toxicity of heavy metals should be
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considered, rather than the activities of individual metal. Also, determining the effects
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of individual heavy metals on the microbial community under field conditions is
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likely to give false conclusions when other metals are also present.
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Acknowledgements
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This work was financially supported by the National Natural Science Foundation of
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China (41721001, 41722111), the National Key R&D Program of China
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(2016YFD0801105), the Science and Technology Program of Zhejiang Province
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(2018C03028), and China Agriculture Research System. We also thank the valuable
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Fig. 1. The relationship between ATP and biomass C contents in field soils
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contaminated with heavy metals. n = 3, p < 0.01.
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Fig. 2. The equations and correlations between biomass C and (a) Cd, (b) Cu, (c) Zn.
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(d) (Cd, Cu, Zn) and biomass C in 3D graph. Data normalization of Cd, Cu and Zn
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(Cd+Cu+Zn = 100) in Fig. 2 (d).
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Fig. 3. (a) Redundancy analysis (RDA), (b) Variation partition analysis (VPA) and
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Mantel test of bacterial community in field experiment. TN: total nitrogen; TC: total
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carbon. Cd, Cu and Zn are total metal contents. n = 3.
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Fig. 4. Biomass C (a) and ATP (b) contents in heavy metal amended soils. The
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horizontal line is the untreated control soil set at 100 %. (Low, medium and high
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respectively indicate the concentrations of heavy metals added to soil, n = 3).
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Different letters indicate significant differences between the same heavy metal
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treatments, P < 0.05; * significant different from the control, P < 0.05 (Tukey
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HSD-test).
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Fig. 5. Relative abundances of the dominant phyla in field and laboratory experiment.
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Relative abundances are based on the proportional frequencies of DNA sequences that
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could be classified. Cd3 signifies soil treated with high Cd concentration, other
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treatments are also soils treated with high concentrations of heavy metals.
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Fig. 6. (a) Redundancy analysis (RDA), (b) Variation partition analysis (VPA) of the
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bacterial community in soils amended with heavy metals and their combinations. (a)
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TCd: total Cd; TZn: total Zn; TCu: total Cu; ACd: available Cd; AZn: available Zn;
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ACu: available Cu. Cd3 means soil treated with high concentration of Cd, other
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treatments are also soils treated with high concentrations of heavy metals. (b) The
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encircled, linear and triangle symbols represent the degree of explanation of the
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changes of the bacterial community by the individual heavy metals, the interaction of
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respectively. Undefined values in the rectangle indicate the contribution of other
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factors to changes in the bacterial community.
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Fig. 3.
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Fig. 4.
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Fig. 6.
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Table 1. Heavy metal concentrations and physicochemical properties of field soils.
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Results are means and S.D of 3 replicates. Different letters indicate the difference are
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significant between treatments at p < 0.05 level.
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Site 1 2 3 4 5
Table 1.
Cd
Cu
Zn
TC
mg kg-1 0.28 ± 0.01e 0.36 ± 0.02d 0.48 ± 0.02c 0.85 ± 0.02b 1.43 ± 0.01a
TN g kg-1
82.0 ± 2.0d 121.4 ± 4.2c 151.2 ± 2.9b 116.7 ± 5.2c 511.4 ± 8.6a
142.9 ± 1.6d 157.9 ± 3.3c 148.3 ± 3.8cd 203.6 ± 5.2b 284.4 ± 6.3a
27.8 ± 0.2c 2.96 ± 0.01b 9.39 ± 0.04c 27.9 ± 0.1c 2.70 ± 0.05d 10.34 ± 0.16b 19.6 ± 0.1d 1.91 ± 0.01e 10.24 ± 0.03b 31.6 ± 0.2b 3.10 ± 0.01a 10.21 ± 0.03b 32.1 ± 0.1a 2.85 ± 0.02c 11.27 ± 0.02a
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pH 4.51 ± 0.02c 4.52 ± 0.01c 5.04 ± 0.03b 5.06 ± 0.02b 5.21 ± 0.03a
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3. Effect of Cu on microbial biomass and bacterial community greater than
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S0269-7491(18)32107-9
DOI:
10.1016/j.envpol.2018.09.011
Reference:
ENPO 11553
To appear in:
Environmental Pollution
Received Date: 11 May 2018 Revised Date:
15 August 2018
Accepted Date: 3 September 2018
Please cite this article as: Song, J., Shen, Q., Wang, L., Qiu, G., Shi, J., Xu, J., Brookes, P.C., Liu, X., Effects of Cd, Cu, Zn and their combined action on microbial biomass and bacterial community structure, Environmental Pollution (2018), doi: 10.1016/j.envpol.2018.09.011. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Graphic abstract
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Effects of Cd, Cu, Zn and their combined action on microbial
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biomass and bacterial community structure
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Jiuwei Song, Qunli Shen, Lu Wang, Gaoyang Qiu, Jiachun Shi, Jianming Xu,
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Philip C. Brookes, Xingmei Liu*
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Institute of Soil and Water Resources and Environmental Science, College of
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Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of
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Agricultural Resources and Environment, Zhejiang University, Hangzhou 310058, P.R.
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China
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AUTHOR INFORMATION
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Corresponding Author
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*Dr. Xingmei Liu
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College of Environmental and Natural Resource Sciences, Zhejiang University,
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Hangzhou 310058, China;
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*phone: +86-571-8898-2419; fax: +86-571-8898-2419; e-mail: [email protected].
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Abstract: Heavy metal pollution can decrease the soil microbial biomass and
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significantly alter microbial community structure. In this study, a long-term field
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experiment (5 years) and short-term laboratory experiment (40 d) were employed to
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evaluate the effects of heavy metals (Cd, Cu, Zn), and their combinations at different
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concentrations, on the soil microbial biomass and the bacterial community. The ranges
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of heavy metal concentration in the long-term and short-term experiments were
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similar, with concentration ranges of Cd, Cu and Zn of about 0.3-1.5, 100-500, and
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150-300 mg kg-1, respectively. Microbial biomass decreased with increasing soil
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heavy metal concentrations in both the long-term and short-term experiments. The
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interaction between soil physicochemical factors (pH, TN, TC) and heavy metals (Cd,
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Cu, Zn) played a major role in change in the bacterial community in long-term
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polluted soil. In the laboratory experiment, although each heavy metal had an adverse
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effect on the microbial biomass and community structure, Cu appeared to have a
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greater role in the changes compared to Cd and Zn. However, the synergistic effects
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of the heavy metals were greater than those of the single metals and the synergistic
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effect between Cu and Cd was greater than that of Cu and Zn.
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Capsule abstract: In a soil containing a combination of Cd, Cu and Zn, Cu has the
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major influence on microbial biomass and the bacterial community.
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Keywords: Heavy metals, Biomass C, ATP, Bacterial community
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1. Introduction
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There is increasing concern about soil pollution by heavy metals because of their
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toxicity to plants, animals and human beings and their lack of biodegradability. The
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anthropometric release of potentially toxic elements currently exceeds the inputs of
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heavy metals from global weathering processes, which has a significant impact on the
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decrease microbial biomass (Brookes and McGrath, 1984; Wang et al., 2007; Giller et
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al., 2009) and inhibit soil enzyme activities in heavy metal polluted soils (e.g.
60
Wyszkowska et al., 2012). In soil ecosystems, microbes play important roles in
61
nutrient cycling, organic matter decomposition and plant nutrient utilization (e.g.
62
Stockdale and Brookes, 2006: Geisseler et al., 2010). Microbial properties, e.g. soil
63
microbial biomass, diversity and activity of soil microbial communities, are
64
commonly used as indicators of metal pollution, due to their high sensitivity to
65
metal-induced stress (Epelde et al., 2009; Pardo et al., 2014) and rapid response to
66
disturbances, their ecological relevance and ability to provide information on the
67
integration of many environmental factors (Bloem et al., 2006; Garbisu et al., 2011).
68
Previous studies showed that heavy metal contamination has both long-term (Lorenz
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et al., 2006; Oliveira and Pampulha, 2006) and short-term (Bouskill et al., 2010; Ding
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et al., 2017) toxicity effects on terrestrial microbial communities.
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Comparisons of the results of long-term field experiments and short-term
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laboratory studies on the toxicity of heavy metals to microbes need to be interpreted
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with caution (Giller et al., 2009). The main reason for possible difference is,
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presumably, that changes in microbial properties are the result of multiple factors,
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such as soil physicochemical properties and, most importantly, small but frequent
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inputs of toxic pollutants (Frossard et al., 2017; Zhao et al., 2016) over the long-term
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(chronic changes) compared to much larger short-term (acute changes) inputs in
78
laboratory experiments. However this has still not been resolved in the two different
79
experimental approaches. Soil physicochemical properties (e.g. soil organic matter,
80
moisture, pH, soil type, etc.) not only influence the toxicity of heavy metals, but also
81
contribute to shifts in microbial community structure (Stemmer et al., 2007; Kenarova
82
et al., 2014) . Therefore, it is important to evaluate the long-term and short-term
83
effects of heavy metals on microbial biomass and the microbial community in soils of
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similar physicochemical properties. In recent years, there have been many studies
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showing the shifts of bacterial community caused by heavy metals under long-term
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ACCEPTED MANUSCRIPT pollution (Chodak et al., 2013; Stefanowicz et al., 2012). For example, soil metal
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pollution significantly shifted the bacterial community composition due to As, Cd and
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Pb contamination (Li et al., 2016). Yao et al. (2017) found significant correlations
89
between microbial community profiles and a combination of Co, Zn, Hg, As and Se
90
concentrations in sediments. The effects of heavy metal interactions between Cd, Cu,
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and Zn on microbial enzyme activity and biomass were previously studied in
92
short-term experiments (Renella et al., 2003; Sharma et al., 1999). Renella et al. (2003)
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also showed that Cu and Zn showed synergistic increases on the effects of Cd toxicity
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on the activities of acid and alkaline phosphatase and soil ATP contents. However,
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apart from a few exceptions, most of the above research was focused on the effects of
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single metals or mixtures of metals on soil microbes and much less on interactions
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between different metals. This is addressed in our research.
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High-throughput sequencing techniques, such as Illumina sequencing of 16s rRNA
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amplicons, provide an effective resolution method to study the phylogenetic
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composition of microbial communities (Caporaso et al., 2011). The V4 region, widely
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supported as a standard 16s rRNA region, has been accepted by the Earth
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Microbiology Project for general microbial community assessment in a range of very
103
different environments (Gilbert et al., 2014). Redundancy analysis (RDA) and
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variation partition analysis (VPA) are increasingly employed to analyze the
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contribution of environmental factors on soil microbial communities (Chen et al.,
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2016; Liu et al., 2017). In the present study, particular emphasis is placed on the novel
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use of the above technologies in determining the effects of heavy metals and other
108
environmental factors on soil bacterial communities. This is the first study that has
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compared the results of long-term field experiments and short-term laboratory studies
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on the toxicity of heavy metals on soil microbes, specifically to better understand the
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interaction between Cu, Cd and Zn.
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The main objective were to simultaneously investigate and compare the effects of
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Cd, Cu, Zn and their combined action on microbial biomass and bacterial community
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hypothesis was heavy metals have significant negative effects on microbial biomass
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and bacterial communities, and there are significant interactions between different
117
metals.
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2. Materials and methods
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2.1. Soil characterization and experimental design
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2.1.1. Field Experiment
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The experimental soils were taken from the Wenling region, Zhejiang Province,
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China. Each was sampled from the surface layer (0-15 cm depth) of five different
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paddy fields (non-flooded) from Wenling, each contaminated with heavy metals.
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Random samples were taken from each field, initially to determine the concentration
125
gradients of Cd (Cd1-Cd5), ranging between 0.3-1.5 mg Cd kg-1 soil. After collection,
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the soils were sieved moist < 2mm, soil moisture adjusted to 40% of water holding
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capacity (WHC) then incubated at 25 oC for 7 d prior to determination of microbial
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biomass carbon (biomass C), ATP and community structure. The heavy metal contents
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in the soils from the selected sites were determined after air drying and finely grinding
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< 100 mesh. The pH (1: 2.5 soil: water) range was 4.51-5.21, organic C 1.96-3.21%,
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total N contents 0.19-0.31% and the C/N ratios 9.39-11.27 in the soils of the five sites
132
respectively. The soil was a loamy clay. Soil Cd, Cu and Zn concentrations and
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physicochemical properties in the soils of the five sites are given in Table 1 and other
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heavy metals concentrations and soil inorganic nutrients in Supplementary Table S1.
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2.1.2. Laboratory Experiment
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Three different concentrations of Cd, Cu, Zn as sulfate and their combinations were
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added to soils already contaminated with the lowest Cd content (Cd1). There were 22
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treatments, including control; 0.5, 1.0, 1.5 mg kg-1 Cd added (Cd1, Cd2, Cd3); 100,
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250, 400 mg kg-1 Cu added (Cu1, Cu2, Cu3); 150, 200, 250 mg kg-1 Zn added (Zn1,
ACCEPTED MANUSCRIPT Zn2, Zn3); and their combinations (Cd+Cu, Cd+Zn, Cu+Zn, Cd+Cu+Zn) at low,
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medium and high concentrations (the concentrations of Cd, Cu and Zn in the
142
combinations were the same as those of the single heavy metals). Soil moisture was
143
adjusted to 40% WHC, and 12.5 g kg-1 of corn powder (40% C；0.7% N ) and 2.86 g
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kg-1 of ammonium nitrate (N content 35%) were added to the soils to provide
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additional C and N as substrates. The soil samples (moist soil containing 500 g
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oven-dry soil) were incubated in air tight 1 L jars at 25 ℃ for 40 d in darkness. The
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jars were opened every 2 d to permit aeration, water added to adjust to constant
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weight and the soils sampled at 40 d of incubation for microbial measurements.
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2.2. Biomass C measurements
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Soil microbial biomass C was determined by the chloroform fumigation-extraction
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method (Vance et al., 1987; Wu et al., 1990). Moist soil (previously treated as above)
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containing 10 g oven dry soil was fumigated with alcohol free chloroform for 24 h at
153
25 ℃ in the dark and the CHCl3 then removed with a vacuum pump. Another part of
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the soil was not fumigated and incubated under the same conditions. The soils were
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then extracted with 40 mL 0.5 M K2SO4 at 220 rpm for 30 min and filtered (Whatman
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42 filter). Finally the filtrates were adjusted to pH 2-3 with HCl, and total organic
157
carbon (TOC) determined using a Total Organic Carbon Analyzer TOC-V/CPN (Multi
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N/C 2100, Germany). Microbial biomass C was calculated from: biomass C = (Cf -
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Cnf)/kEc, where Cf is total organic C extracted from fumigated soil; Cnf is total
160
organic C extracted from non-fumigated soil and kEc (the proportion of biomass C
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extracted following fumigation is 0.45 (Vance et al., 1987; Wu et al., 1990).
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2.3. ATP measurements
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ATP was extracted from the soils (Jenkinson and Oades, 1979) on the same day as
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the microbial biomass C measurements. At each time, three replicates of moist soil,
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each containing 3 g oven-dry, were taken from each treatment and weighed into 50
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mL centrifuge tubes. These soils were each ultrasonified with 25 mL of extractant A
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(Redmile-Gordon et al., 2011) for 2 min. A further three soil portions of each
169
treatment were ultrasonified with 25 mL of extractant B (extractant A containing
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5×10-4 M ATP). The soil suspensions were then cooled on ice for about 10 min then
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filtered through Whatman 42 filter papers. Measurement of ATP was done using a
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bioluminometer, with the fire-fly luciferin-luciferase reagent (Qiu et al., 2016).
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2.4. Heavy metal measurements
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The concentrations of total heavy metals in the soils were determined by an
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ICP-MS (inductively coupled plasma mass spectrometer). The soil was air-dried and
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sieved < 100 mesh. Soil (0.20 g) was subjected to microwave digestion with 4 mL
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concentrated HNO3 and 2 mL HF. Available soil heavy metals were also determined
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by ICP-MS following extraction of 5 g soil with 50 mL 0.01 M CaCl2 after shaking
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for 2 h at 250 rpm.
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2.5. Bacterial 16S rRNA Gene Amplification, Illumina Sequencing, and Data
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Processing
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The field soils and some short-term heavy metal contaminated soils were selected
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for DNA extraction. Total genome DNA from soils (0.5 g) was extracted using a Fast
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DNA Spin Kit (MP Biomedical, France) following the manufacturer’s instructions.
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The concentration and purity of DNA were determined on 1% agarose gels. The 16S
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rRNA genes of the V4 regions were amplified using a specific primer (515F-806R).
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The forward primer was 515F (5’-GTG CCA GCM GCC GCG GTA A-3’), and the
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reverse primer consisted of a seven bp barcode and 806R (5’-GGA CTA CHV GGG
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TWT CTA AT-3’). The purified amplicons were then sequenced on an Illumina Miseq
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sequencing platform (Illumina Inc., San Diego, CA, USA) at Novogene Co., Ltd,
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Beijing, China. Sequence analyses were carried out by Uparse software (Uparse
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v7.0.1001, http://drive5.com/uparse/) (Edgar, 2013). Sequences with ≥ 97% similarity
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were assigned to the same OTUs. Representative sequences of each OTU were
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ACCEPTED MANUSCRIPT screened for further annotation. The RDA, Mantel test results, and VPA were
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calculated from the R package vegan (Oksanen et al., 2012). The dataset of 16S rRNA
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gene sequences were deposited in NCBI’s Sequence Read Archive (SRA) with
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accession numbers SRP142650 and SRP142656 respectively.
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2.6. Data analyses
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All data were analyzed using Origin 9.0 and SPSS 20.0 software. One-way
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ANOVA was used to analyze the treatment effects. Differences with values of P <
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0.05 were considered statistically significant. All analytical data are the means of
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triplicate determinations.
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3. Results
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3.1. The relationship between ATP and biomass C in field experiment
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There was a significant linear correlation between ATP and biomass C
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concentrations in the heavy metal polluted field soils (R2 = 0.80, Fig. 1). The contents
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of ATP and biomass C decreased linearly from site 1 to site 5. Soil ATP ranged from
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2.06 to 5.00 nmol g-1 soil, and biomass C from 287.4-770.8 µg g-1 soil. The mean
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biomass ATP concentration was 5.82 µmol g-1 biomass C.
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3.2. Effects of heavy metals on biomass C in field experiment
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correlated with the power functions (Fig. 2). Total Cd had the strongest negative
213
relationship with biomass C, with a correlation coefficient of 0.92 (Fig. 2a). The
214
relationship between Cu and biomass C was the weakest, albeit with a statistically
215
significant correlation coefficient of 0.77 (Fig. 2b). When heavy metal concentrations
216
were high, the biomass C content was low, and vice versa (Fig. 2d). Because all the
217
soils contained Cd, Cu and Zn, it was not possible to determine if the results were due
218
to single metals or metal-metal interactions.
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3.3. Effects of soil physicochemical properties and heavy metals on bacterial
220
communities in the field experiment In the field experiment, the changes in the bacterial community were clearly
222
affected by heavy metals and soil physicochemical properties. The first two
223
environmental factors of RDA accounted for 77.44% of the changes in the soil
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bacterial community (Fig. 3a), with RDA1 explaining 61.01% of the changes. It is
225
difficult to determine which individual factors played key roles in the changes in the
226
bacterial community because pH, Cd, Zn and Cu all had small angles with the RDA1
227
axis. The angles between TN (total nitrogen), TC (total carbon) and the RDA2 axis
228
were small, and RDA2 explained 16.43% of the changes in the soil bacterial
229
community.
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VPA was used to calculate the relationships between soil physicochemical factors
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(pH, TN, TC) and the Cd, Cu and Zn contents to explain the changes in bacterial
232
community structure (Fig. 3b). The total variance of 78.36% for bacteria was
233
explained by the soil physicochemical factors and the amount of heavy metals, and
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their interaction explained 48.16% of the variations. The individual effects of soil
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physicochemical factors and the amount of heavy metals accounted for 15.08% and
236
15.12% respectively of the variations in the bacterial community. The Mantel test
237
further confirmed the correlation between these factors and the bacterial community.
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3.4. Changes of biomass C and ATP contents in heavy metal amended soil
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Different combinations of heavy metals were added to the field soil with the lowest
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Cd concentration (Cd1). After 40 d incubation, the biomass C and ATP contents were
241
determined. The biomass C contents in soils with high concentrations of Cu+Zn and
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Cd+Cu+Zn decreased significantly compared to the control soil, (-22.24% and
243
-34.13% respectively) (Fig. 4a). With the Cu and Zn treatments, biomass C content
244
decreased with increasing heavy metal concentrations. However, it did not decrease
245
significantly with increasing soil total Cd contents (Fig. 4a).
ACCEPTED MANUSCRIPT In the field experiment, the ATP contents in the Cd+Cu+Zn treatments at high
247
concentrations significantly decreased by 56.1% compared to the control soil (Fig. 4b).
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With Cd+Zn, Cu+Zn, and Cd+Cu+Zn treatments, soil ATP contents also decreased
249
significantly with increasing heavy metals concentrations. However, there were no
250
significant differences between the ATP contents of single heavy metals (Cd, Cu, Zn
251
only) between the heavy metals concentration increases. The mean biomass ATP
252
concentration was 13.30 µmol ATP g-1 biomass C, and the two parameters were
253
significantly correlated (p < 0.01) (Supplementary Figure S2).
254
3.5. Bacterial community composition in field and laboratory experiments
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The 7 dominant phyla of bacterial community both in long-term and short-term
256
contaminated soils were selected to determine the effects of heavy metals. The main
257
phyla were: Proteobacteria, Actinobacteria, Acidobacteria and Chloroflexi (Fig. 5).
258
Proteobacteria was the dominant phylum in both the short and long term heavy metal
259
polluted soil. In the field experiment, the relative abundance of Actinobacteria
260
significantly decreased with increasing heavy metal contents. In the laboratory
261
experiment, the relative abundance of Proteobacteria in all treatments containing Cu
262
was significantly lower than in the control soil. The relative abundance of
263
Actinobacteria in the metal treated soils in the laboratory experiment were
264
significantly higher than in the control and the treatment with the highest
265
concentrations of heavy metals (Cd3+Cu3+Zn3), comprising 30.38% of the total
266
sequences. With the exception of the Cd3 treatment, the relative abundances of
267
Acidobacteria were significantly higher than in the control. The bacterial community
268
composition in field site 5 and the Cd3+Cu3+Zn3 treatments were significantly
269
different, although their heavy metal contents were the same.
270
3.6. Relationship between heavy metals and bacterial community in the laboratory
271
experiment
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In the short-term laboratory incubation experiment, changes in the bacterial
ACCEPTED MANUSCRIPT community were significantly related to the additions of heavy metals (Fig. 6). The
274
first two environmental factors of RDA accounted for 85.26% of the changes in the
275
soil bacterial community (Fig. 6a) and RDA1 explained 69.81%. The angle between
276
Cu (TCu and ACu) and the RDA1 axis was the smallest, and showed a positive
277
correlation with RDA1. The angles between Zn (TZn and AZn), Cd (TCd and ACd)
278
and the RDA2 axis were small, and positively correlated. RDA2 explained 15.45% of
279
the changes in the soil bacterial community.
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VPA was used to calculate the interactions of the three heavy metals (both total and
281
available) on bacterial community changes (Fig. 6b), accounting for 65.85% of the
282
changes. Cd, Cu and Zn explained 8.38%, 18.78% and 10.28% respectively while the
283
slight interactions between Cd and Zn only explained 0.40% of the total variance. The
284
combination of Cd, Cu and Zn did not explain changes in the bacterial community
285
(-3.58%).
286
4. Discussion
287
4.1. The effect of heavy metals on biomass C and ATP in soil
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Brookes and McGrath, (1984) published the first report that heavy metals, at or
289
around current European permitted soil heavy metal limits, decreased the size of the
290
soil microbial biomass in field soils. Our study investigated the separate effects of
291
long-term and short-term heavy metal contamination in both field and laboratory
292
incubations. The significant negative correlations between single metals (Cd, Cu and
293
Zn) and biomass C indicated that each metal separately decreased the biomass C
294
concentrations in the field experiment (Fig. 2). Despite the low Cd concentrations in
295
the field soil it apparently produced the most significant negative correlation with
296
biomass C (Fig. 2a). However, this analysis takes no account of possible interactions
297
between biomass C and synergistic effects of soil heavy metals. These results contrast
298
markedly with those from the short term laboratory experiment (Fig. 4a). The
299
threshold values of Cd, Cu and Zn given by the Chinese Environmental Quality
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ACCEPTED MANUSCRIPT Standard for Soils for agricultural soils are 0.3, 50 and 200 mg kg-1, respectively (GB
301
15618-1995). In both experiments, the ranges of soil heavy metal concentrations were
302
comparable. In the field experiment the maximum concentrations were 300 Zn, 500
303
Cu and 1.5 mg Cd kg-1 soil, and in the laboratory experiment, 250, 400 and 1.5 mg
304
kg-1 soil respectively. However, unlike in the field experiment there were no changes
305
in biomass C at lower metal concentrations in the laboratory experiment. The main
306
responses were marked declines in biomass C in the high Cd+Zn treatments and in the
307
high Cd+Cu+Zn treatments (Fig. 4). These results indicate the need for caution when
308
comparing results from chronic long-term effects of heavy metals in the field with
309
those from acute short-term laboratory experiments (Giller et al., 2009). Renella et al.
310
(2002) also indicated that the effects of long-term field exposure to metal toxicity
311
cannot be inferred by using heavy metal salts in short-term studies, at least as far as
312
impacts on the microbial biomass are concerned. However the results from the
313
short-term laboratory experiment clearly indicated that interactions between metals
314
produced significant decreases in biomass while single metals did not. This showed
315
that there is an additive or synergistic effects between heavy metals, which is
316
consistent with Sharma et al. (1999). The long-term field experiment also
317
demonstrated that it is inadvisable to base heavy metal effects on the analysis of a
318
single metal. For example, as discussed above, in the long-term field experiment, the
319
strongest negative correlation between biomass C and heavy metals was with Cd. Yet,
320
in the laboratory experiment, Cd had no significant negative effect on biomass C
321
unless in combination with other metals (Fig. 4a).
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Soil ATP measurements also provide a good index of soil microbial biomass
323
(Jenkinson et al., 1988; Contin et al., 2001) in both substrate amended and non
324
amended soils. Following short term additions of heavy metals to soil, again only the
325
combination of Cd, Cu, and Zn decreased soil ATP contents, while the other
326
treatments (single heavy metal and two heavy metals combination) had no negative
327
effects. This supports the above argument. Both Jenkinson et al., (1988) and Contin et
328
al. (2001) compiled correlated ATP and biomass C then available in the literature and
ACCEPTED MANUSCRIPT found that the biomass ATP concentrations were about 11.7 and 11.0 µmol g-1 biomass
330
C, respectively. However, the concentrations of biomass ATP covered a reasonably
331
wide range, from about 6 to 14 µmol g-1 biomass C (Contin et al., 2001). The average
332
concentration of biomass ATP in soils contaminated by heavy metals in our field
333
experiment was 5.82 µmol g-1 biomass C, which is very close to the biomass ATP
334
concentration of 7.18 measured by Brookes and McGrath (1984) in heavy metal
335
contaminated soils. However, the mean biomass ATP concentration was 13.30 µmol
336
g-1 biomass C in the short-term laboratory experiment, which was much higher than in
337
the field experiment (Fig. S2 and Fig. 1). We tentatively offer the following
338
hypothesis. In contaminated soil, microbes need more energy to survive under adverse
339
conditions (Mikanova, 2006). Zhang et al. (2010) also demonstrated that heavy metal
340
stress enhanced the energy expenditure of microbes and increased microbial
341
respiration. Microbial communities in contaminated soils would be expected to evolve
342
as integrated systems adapted to local environmental gradients of anthropogenic stress
343
(Hoostal et al., 2008), because genes associated with metabolic responses to
344
environmentally selective agents (such as heavy metals) are usually found in plasmids
345
and can be transferred laterally among distantly related taxa within microbial
346
communities (Coombs and Barkay, 2004). When microbes first come into contact
347
with heavy metals, it is possible that, because of their increased metabolic expenditure,
348
the ATP content increases and the microbial biomass, providing an endocellular
349
energy source, decreases, which would account for this discrepancy. Over time, the
350
microbes apparently adapted to heavy metal stress, and the microbial community and
351
the biomass ATP contribution reverted to more usual published levels. This may
352
explain why the biomass ATP concentration in the short-term experiment differed
353
from the long-term experiment. Further work should be done to clarify this
354
phenomenon.
355
4.2. The effects of heavy metals on the bacterial community
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The toxicity of heavy metals to bacterial communities is greater than to fungi
ACCEPTED MANUSCRIPT (Rajapaksha et al., 2004). The bacterial community was dominated by four major
358
groups (Proteobacteria, Actinobacteria, Acidobacteria and Chloroflexi) in the different
359
heavy metals treatments (Fig. 5). These four dominant phyla accounted for nearly
360
80% of the total bacterial abundance both in the field and laboratory experiments.
361
Proteobacteria is considered to be the dominant bacteria in the heavy metal
362
contaminated soil (Idris et al., 2004). There was also a significant increase in the
363
relative abundance of Acidobacteria in the heavy metal contaminated soils at the
364
phylum level, which is also consistent with previous studies (Li et al., 2017).
365
Compared with the control, the relative abundance of Chloroflexi in all soils treated
366
with Cu in the short-term experiment were significantly higher, and consistent with Li
367
et al. (2015) in soils of pH 4-4.5. However, the bacterial community composition in
368
site 5 and Cd3+Cu3+Zn3 treatments were significantly different, although their heavy
369
metal contents were the same. Li et al. (2015) found that the bacterial communities
370
changed over time in Cu contaminated agricultural soils, and the site effect is
371
presumed to be the determinant factor in microbial community shifts (Macdonald et
372
al., 2011).
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In the field experiment, the bacterial community was affected by pH, Cd, Zn and
374
Cu contents, and TN and TC also contributed. (Fig. 3a). The shifts in bacterial
375
community structure therefore depend not only on heavy metals concentrations but
376
also on other factors e.g. soil organic matter, moisture, pH and soil type (Boivin et al.,
377
2006; Kenarova et al., 2014). Li et al. (2017) showed that heavy metals were the most
378
important factors affecting the microbial community compared with other factors (e.g.
379
pH, soil C and N). Zhang et al. (2016) demonstrated that heavy metals could mask the
380
effect caused by soil physicochemical properties in wetland soil. However, in
381
metal-contaminated forests the structure of the soil microbial community was shown
382
to be principally dependent on soil pH (Chodak et al., 2013). Similarly Jiang et al.,
383
(2016) showed reported that soil pH, rather than Cu concentration, was the main
384
factor affecting the bacterial community). Our results showed that 78.36% of the
385
bacterial community changes could be explained by soil physicochemical factors (pH,
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ACCEPTED MANUSCRIPT TN, TC). The amount of heavy metals (Cd, Cu, Zn), and their interaction explained
387
48.16% of the changes in the bacterial community (Fig. 3b). This indicates that the
388
changes in the bacterial community was mainly the result of the interactions of soil
389
physicochemical factors (pH, TN, TC) and heavy metals (Cd, Cu, Zn). The Mantel
390
test results further confirmed that these factors were significantly related to the
391
bacterial community.
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In our laboratory experiment, we used the same soil as in the field experiment and
393
the soil properties hardly changed after the addition of heavy metals. Therefore we
394
can directly compare the effects of heavy metals on the different bacterial
395
communities. RDA1 explained 69.81% of the changes in the soil bacterial community
396
following the addition of heavy metals, while the angle between total or available Cu
397
was very small (Fig. 6a). All the Cu treatment data points converged, and the
398
community structure was greatly affected by Cu. VPA showed that the order of the
399
individual contribution rates of heavy metals to the changes in the bacterial
400
community were Cu > Zn > Cd in the laboratory experiment, which contributed
401
18.78%, 10.28% and 8.38% respectively (Fig. 6b). It has been previously shown that
402
Cu contamination can exert a large effect on soil microbial biomass, enzyme activity,
403
and soil microbial community (Li et al., 2015; Wang et al., 2007). The probable
404
reason why Cu made the largest contribution is that Cu not only binds to enzyme
405
molecules, but also enzyme-substrate complexes, both of which result in decreased
406
enzyme activities (Huang and Shindo, 2000). High Cu concentrations may lead to the
407
formation of reactive oxygen species and subsequent oxidative stress, and also to the
408
oxidation of protein, DNA and lipids, resulting in cell death and changes in microbial
409
community structure (Li et al., 2014). The interaction between Cd and Cu explained
410
23.08% of the bacterial community while Cd and Zn explained only 0.40% (Fig. 6b).
411
Our results suggested that Cu and Cd have synergistic effects on bacterial community
412
changes. This is consistent with the result that the additive effect of Cu and Cd is
413
significantly greater than that of Zn and Cd in affecting soil microbes (Renella et al.,
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2003). The competition of Cd and Zn for adsorption sites has been reported
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ACCEPTED MANUSCRIPT previously (Christensen, 1987). In our experiment, because the available Zn content
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was much higher than that of available Cd, Zn would dominate in the competition
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between Zn and Cd. When the three heavy metals were applied together, the
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synergistic effect between Cu and Cd was inhibited, while that between Cu and Zn
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was enhanced. The combination of the three heavy metals caused little change to the
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bacterial community (-3.58%). The change was mainly a result of the toxicity of
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single heavy metal and the synergistic effects between Cd-Cu and Cu-Zn.
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5. Conclusions
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The long-term effects of heavy metals on microbes in the environment cannot be
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duplicated in short-term laboratory experiments. The interactions between soil
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physicochemical factors (pH, TN, TC) and heavy metals (Cd, Cu, Zn) play a major
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role in changes in the bacterial community in long-term polluted soil. At the heavy
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metals concentration applied in the laboratory experiment, the effects of Cu on the
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microbial biomass and bacterial community were greater than Cd and Zn. Although
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Cd had no significant effect on the microbial biomass below 1.5 mg kg-1, the
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synergistic effect between Cd and Cu made a significant difference to the bacterial
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community. There was also a competitive relationship between Cd and Zn. Therefore,
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should heavy metal standards be applied in the future for soil microbes, these results
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suggest that it is important that the combined toxicity of heavy metals should be
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considered, rather than the activities of individual metal. Also, determining the effects
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of individual heavy metals on the microbial community under field conditions is
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likely to give false conclusions when other metals are also present.
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Acknowledgements
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This work was financially supported by the National Natural Science Foundation of
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China (41721001, 41722111), the National Key R&D Program of China
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(2016YFD0801105), the Science and Technology Program of Zhejiang Province
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(2018C03028), and China Agriculture Research System. We also thank the valuable
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Fig. 1. The relationship between ATP and biomass C contents in field soils
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contaminated with heavy metals. n = 3, p < 0.01.
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Fig. 2. The equations and correlations between biomass C and (a) Cd, (b) Cu, (c) Zn.
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(d) (Cd, Cu, Zn) and biomass C in 3D graph. Data normalization of Cd, Cu and Zn
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(Cd+Cu+Zn = 100) in Fig. 2 (d).
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Fig. 3. (a) Redundancy analysis (RDA), (b) Variation partition analysis (VPA) and
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Mantel test of bacterial community in field experiment. TN: total nitrogen; TC: total
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carbon. Cd, Cu and Zn are total metal contents. n = 3.
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Fig. 4. Biomass C (a) and ATP (b) contents in heavy metal amended soils. The
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horizontal line is the untreated control soil set at 100 %. (Low, medium and high
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respectively indicate the concentrations of heavy metals added to soil, n = 3).
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Different letters indicate significant differences between the same heavy metal
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treatments, P < 0.05; * significant different from the control, P < 0.05 (Tukey
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HSD-test).
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Fig. 5. Relative abundances of the dominant phyla in field and laboratory experiment.
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Relative abundances are based on the proportional frequencies of DNA sequences that
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could be classified. Cd3 signifies soil treated with high Cd concentration, other
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treatments are also soils treated with high concentrations of heavy metals.
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Fig. 6. (a) Redundancy analysis (RDA), (b) Variation partition analysis (VPA) of the
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bacterial community in soils amended with heavy metals and their combinations. (a)
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TCd: total Cd; TZn: total Zn; TCu: total Cu; ACd: available Cd; AZn: available Zn;
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ACu: available Cu. Cd3 means soil treated with high concentration of Cd, other
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treatments are also soils treated with high concentrations of heavy metals. (b) The
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encircled, linear and triangle symbols represent the degree of explanation of the
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changes of the bacterial community by the individual heavy metals, the interaction of
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respectively. Undefined values in the rectangle indicate the contribution of other
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factors to changes in the bacterial community.
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Fig. 3.
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Fig. 4.
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Fig. 6.
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Table 1. Heavy metal concentrations and physicochemical properties of field soils.
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Results are means and S.D of 3 replicates. Different letters indicate the difference are
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significant between treatments at p < 0.05 level.
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Site 1 2 3 4 5
Table 1.
Cd
Cu
Zn
TC
mg kg-1 0.28 ± 0.01e 0.36 ± 0.02d 0.48 ± 0.02c 0.85 ± 0.02b 1.43 ± 0.01a
TN g kg-1
82.0 ± 2.0d 121.4 ± 4.2c 151.2 ± 2.9b 116.7 ± 5.2c 511.4 ± 8.6a
142.9 ± 1.6d 157.9 ± 3.3c 148.3 ± 3.8cd 203.6 ± 5.2b 284.4 ± 6.3a
27.8 ± 0.2c 2.96 ± 0.01b 9.39 ± 0.04c 27.9 ± 0.1c 2.70 ± 0.05d 10.34 ± 0.16b 19.6 ± 0.1d 1.91 ± 0.01e 10.24 ± 0.03b 31.6 ± 0.2b 3.10 ± 0.01a 10.21 ± 0.03b 32.1 ± 0.1a 2.85 ± 0.02c 11.27 ± 0.02a
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pH 4.51 ± 0.02c 4.52 ± 0.01c 5.04 ± 0.03b 5.06 ± 0.02b 5.21 ± 0.03a
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2. Bacterial community determined by soil properties and HM in field experiment.
3. Effect of Cu on microbial biomass and bacterial community greater than
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Zn and Cd.
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4. Synergism between Cu and Cd greater than Cu and Zn on soil microbes.