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. 2014 Mar;80(6):1874–1881. doi: 10.1128/AEM.02972-13

Ecological Dynamics of Toxic Microcystis spp. and Microcystin-Degrading Bacteria in Dianchi Lake, China

Lin Zhu a,b, Yanlong Wu a,b, Lirong Song a,✉, Nanqin Gan a,✉
Editor: C R Lovell
PMCID: PMC3957655  PMID: 24413601

Abstract

Toxic cyanobacterial blooms directly threaten both human safety and the ecosystem of surface waters. The widespread occurrence of these organisms, coupled with the tumor-promoting properties of the microcystin toxins that they produce, demands action to mitigate their potential impacts and, thus, a robust understanding of their ecological dynamics. In the present work, the abundance of toxic Microcystis spp. and microcystin (MC)-degrading bacteria in Dianchi Lake, located in Yunnan Province, China, was studied using quantitative PCR. Samples were taken at monthly intervals from June 2010 to December 2011 at three sampling stations within this freshwater lake. Results revealed that variation in the abundance of both total Microcystis spp. and toxic Microcystis spp. exhibited similar trends during the period of the algal bloom, including the reinvasion, pelagic growth, sedimentation, and overwintering periods, and that the proportion of toxic Microcystis was highest during the bloom and lowest in winter. Importantly, we observed that peaks in mlrA gene copy numbers of MC-degrading bacteria occurred in the months following observed peaks in MC concentrations. To understand this phenomenon, we added MCs to the MC-degrading bacteria (designated strains HW and SW in this study) and found that MCs significantly enhanced mlrA gene copy numbers over the number for the control by a factor of 5.2 for the microcystin-RR treatment and a factor of 3.7 for the microcystin-LR treatment. These results indicate that toxic Microcystis and MC-degrading bacteria exert both direct and indirect effects on each other and that MC-degrading bacteria also mediate a shift from toxic to nontoxic populations of Microcystis.

INTRODUCTION

Algal blooms are a frequent and problematic feature of many freshwater bodies around the world. Toxic cyanobacterial blooms directly threaten both human safety and the ecological quality of surface waters (1). Hepatotoxic cyanobacterial blooms occur more frequently than neurotoxic blooms (2). In China, most hepatotoxic blooms are caused by cyanobacteria belonging to the genus Microcystis, which produce cyclic heptapeptide hepatotoxin microcystins (MCs). The widespread occurrence of these bacteria, coupled with the tumor-promoting properties of the microcystin toxins that they produce, demands action to mitigate their potential impacts and, thus, a robust understanding of the ecological dynamics of the toxic blooms.

The typing of single colonies by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) (3, 4) can identify toxic and nontoxic Microcystis organisms and is a valuable tool for ecological studies of the genus Microcystis. However, this method requires the use of very expensive equipment that is not always available (3). An alternative approach, using molecular genotyping via PCR techniques, has been successfully applied to the detection of the microcystin biosynthesis mcy gene cluster and has revealed a direct relationship between gene expression and toxin production (5, 6). Quantitative reverse transcription-PCR (qRT-PCR) methods for identifying bacterial entities have also been established for Microcystis and Anabaena (7–9). Furthermore, Janse et al. (10) characterized toxic and nontoxic Microcystis colonies in natural populations using rRNA-internal transcribed spacer denaturing gradient gel electrophoresis (rRNA ITS-DGGE).

Microcystins are stable in water, and microcystin-LR is even resistant to temperatures up to 300°C and to extremes in pH (11). MCs present in water, however, eventually undergo biodegradation and photolysis. Jones et al. (12) isolated the first MC-degrading bacterium, MJ-PV, from Australian water bodies. Since then, large numbers of MC-degrading bacteria have also been isolated from natural water (13–18). In addition, the mlr gene cluster (mlrA, mlrB, mlrC, and mlrD) of the MC-degrading bacterium Sphingomonas sp. strain ACM-3962 has been demonstrated to encode proteins involved in the initial steps of microcystin biodegradation (19, 20). In particular, the mlrA gene has been shown to encode an enzyme responsible for the hydrolytic cleavage of the cyclic structure of MCs (20). Conventional PCR techniques are able to identify the mlrA gene and detect MC-degrading bacteria from field water and from the biofilms of biofilters (21, 22). However, these conventional PCR assays cannot reveal the abundance of the mlrA gene that is present in a sample. Recently, a quantitative mlrA gene-directed TaqMan PCR assay that can rapidly detect MC-degrading bacteria via the use of degenerate oligonucleotides that target conserved DNA regions has been developed (22). In this study, the TaqMan PCR assay was used to quantitatively detect total Microcystis spp., toxic Microcystis spp., and MC-degrading bacteria using primers that target the 16S rRNA gene, mcyD genes, and the microcystin degradation protein-encoding gene (mlrA).

Most previous studies of algal bloom dynamics have focused on their relationship to physicochemical factors affecting growth in the aquatic environment or on quantifying changes in mcy gene copy numbers that occur during blooms (23). To date, little is known about the effects of toxic Microcystis spp. and microcystins on the abundance of MC-degrading bacteria and vice versa. Therefore, this study aimed to characterize the quantitative and qualitative effects of toxic Microcystis and microcystins on MC-degrading bacterial abundance and mlrA gene expression.

MATERIALS AND METHODS

Study site and sampling.

Sampling was conducted at three sampling stations (station D13 [24°57′39.17″N, 102°38′45.40″E], station D22 [24°49′48.00″N, 102°42′47.00″E], and station D24 [24°41′58.00″N, 102°39′53.00″E]) in Dianchi Lake, the largest lake (300 km2) in China's Yunnan Province (Fig. 1). Dianchi Lake is a plateau lake that has a very small watershed for a relatively large water surface area. Sampling stations were visited once a month from June 2010 to December 2011. Water samples were collected from a depth of 0.5 m using a van Dorn bottle. The van Dorn bottle was oriented vertically for sampling. Water samples (50 ml) were filtered through 0.22-μm-pore-size polycarbonate membrane filters (Xinya Factory, Shanghai, China), transported on ice, and stored at −20°C prior to DNA extraction. Samples used for MC detection were filtered through a 0.45-μm-pore-size glass fiber membrane (Jingteng, China). Ten milliliters of this filtrate was stored at −20°C.

FIG 1.

FIG 1

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Map showing sampling stations in Dianchi Lake, Yunnan Province, China: site D13, 24°57′39.17″N, 102°38′45.40″E; site D22, 24°49′48.00″N, 102°42′47.00″E; site D24, 24°41′58.00″N, 102°39′53.00″E.

Microcystin analysis.

Dissolved microcystins were measured in duplicate using an enzyme-linked immunosorbent assay (ELISA) kit (manufactured by the Institute of Hydrobiology [IHB], Chinese Academy of Sciences [CAS], China). The ELISA kit used a microcystin monoclonal antibody that reacts with most microcystin variants as well as with microcystin-LR and had a detection limit of 0.1 μg/liter. Further details regarding the use of the ELISA are provided by Lei et al. (24).

DNA extraction.

DNA extraction from Microcystis was performed according to the protocol of Rinta-Kanto et al. (8), with slight modification. Briefly, sterilized scissors were used to fragment (cut) the filtrated membranes into sections that were suspended in 2 ml of lysis buffer (10 mM Tris, 100 mM NaCl, 1 mM EDTA, pH 9) and stirred constantly with a pipette tip to ensure complete separation of the filter. To this we then added 20 μl of lysozyme (100 mg/ml) and incubated the solution at 37°C for 20 min. After incubation, 6 μl of proteinase K (20 mg/ml) and 105 μl of 10% sodium dodecyl sulfate (SDS) were added, and the cell suspension was then incubated at 50°C for 2 h. DNA was extracted by adding a volume of phenol-chloroform-isoamyl alcohol (25:24:1) equal to the volume of the aqueous phase, mixing the solution gently for 2 min, and then centrifuging the solution at 11,000 rpm for 20 min. A subsequent extraction of the aqueous phase was then undertaken, adding an equal volume of chloroform-isoamyl alcohol (24:1), mixing the solution, and again centrifuging at 11,000 rpm for 20 min. The upper aqueous phase was transferred to a new tube to which absolute ethanol (2× the aqueous-phase volume) and 10 M ammonium acetate (0.1× the aqueous-phase volume) were then added. This mixture was precipitated overnight (at −20°C). Following centrifuging at 11,000 rpm for 30 min, the supernatant was removed and the precipitated DNA was washed with cold 70% ethanol and then centrifuged again at 11,000 rpm for 10 min. DNA pellets were air dried and subsequently resuspended in 50 μl deionized, distilled water and stored at −20°C. The concentration and purity of the extracted DNA were measured with a spectrophotometer (NanoDrop Technologies, Wilmington, DE). This process was repeated in triplicate for each sample.

DNA extraction from MC-degrading bacteria, meanwhile, was undertaken with a PowerWater DNA isolation kit (Mo Bio Laboratories Inc., Carlsbad, CA) according to the manufacturer's instructions. Again, DNA extraction was repeated in triplicate with three filters for each sample. Each DNA extract was used as the PCR template for quantitative PCR (qPCR).

Standard curve preparation.

To quantify the abundance of total Microcystis spp., toxic Microcystis spp., and MC-degrading bacteria in Dianchi Lake, a qPCR assay was performed using primers based on 16S rRNA genes, mcyD genes, and mlrA genes, according to previously described methods (6, 9, 22). Microcystis aeruginosa PCC7806 was used as the standard strain for the quantification of both total Microcystis spp. and toxic Microcystis spp. The Sphingomonas sp. of MC-degrading bacteria that was isolated from field water was used to quantify the MC-degrading bacteria (25). The standard curve was established by correlating known DNA concentrations (in cell equivalents) with the threshold cycle (CT) values of the diluted samples (26). Ten milliliters of the PCC7806 strain containing 1.71 × 107 cells/ml (determined by a direct microscopic count) was filtered through 0.22-μm-pore-size polycarbonate membrane filters (Xinya Factory, Shanghai, China). A series of 10-fold dilutions (ranging from 3.4 × 106 cells to 3.4 cells) of the PCC7806 DNA template standard solution was used as the external standard for the qPCR. Ten milliliters of the Sphingomonas sp. containing 1.2 × 109 cells/ml (determined by serial dilution of the count obtained by the coated plate method) was collected using the same method used for strain PCC7806. Again, a series of 10-fold dilutions (ranging from 1.2 × 108 cells to 1.2 × 102 cells) of the Sphingomonas sp. was used as the external standard for the qPCR. CT calculations were completed automatically for each qPCR assay using iQ5 software (version 2.0; Bio-Rad, Hercules, CA) and the maximum correlation coefficient approach. In this approach, the threshold is automatically determined to obtain the highest possible correlation coefficient (r2) for the standard curve.

TaqMan quantitative PCR conditions.

We used a Bio-Rad cycler equipped with the iQ5 real-time fluorescence detection system and software (version 2.0; Bio-Rad) to amplify and quantify gene copies. All reactions were completed in a total volume of 20 μl comprising 0.5 mM each primer, 0.1 mM TaqMan probe (Invitrogen, CA), 10 μl Bestar real-time PCR master mix (DBI Bioscience, China), 1 μl bovine serum albumin (3 mg/ml; Sigma), double-distilled H2O, and template DNA. The primers used for amplification of total Microcystis spp., toxic Microcystis spp., and MC-degrading bacteria are listed in Table 1. Three separate assays were performed to quantify the Microcystis 16S rRNA gene, mcyD, and qmlrA for all samples. The qPCR program for Microcystis 16S rRNA and mcyD (toxic Microcystis/total Microcystis) was as follows: 95°C for 2 min, followed by 45 cycles of 95°C for 30 s and 55°C for 1 min. The qPCR program for qmlrA was as follows: 95°C for 2 min, followed by 45 cycles of 95°C for 15 s and 62°C for 45 s. All PCRs were run in triplicate on 96-well plates (Bio-Rad) sealed with optical-quality sealing tape (Bio-Rad). Three negative controls without DNA were included for each PCR run.

TABLE 1.

Oligonucleotides used as primers for qPCR and qRT-PCR

DNA target Primer Sequencea (5′–3′) Reference
Microcystis 16S rRNA 184F GCCGCRAGGTGAAAMCTAA 40
431R AATCCAAARACCTTCCTCCC
Probe (TaqMan) FAM-AAGAGCTTGCGTCTGATTAGCTAGT-BHQ-1 8
mcyD F2 GGTTCGCCTGGTCAAAGTAA 41
R2 CCTCGCTAAAGAAGGGTTGA
Probe (TaqMan) FAM-ATGCTCTAATGCAGCAACGGCAAA-BHQ-1 8
mlrA qmlrAf AGCCCKGGCCCRCTGC 22
qmlrAr ATGCCARGCCCACCACAT
Probe (TaqMan) FAM-TGCCSCAGCTSCTCAAGAAGTTTG-BHQ-1
Bacterial 16S rRNA BACT1369F CGGTGAATACGTTCYCGG 42
PROK1492R GGWTACCTTGTTACGACTT
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a

FAM, 6-carboxyfluorescein; BHQ-1, black hole quencher 1.

RNA extraction, cDNA synthesis, and qRT-PCR amplification.

Two MC-degrading bacteria (designated strains HW and SW) were isolated from field water and identified as a Sphingomonas sp. and a Sphingopyxis sp. HW and SW were cultured with physiological saline and treated without and with MC-LR and MC-RR each day. This was done at a final concentration of 100 μg/liter while the cultures were shaken at 150 rpm at 28°C in a 50-ml glass flask with a volume of 25 ml. Two milliliters of culture was taken from the flasks each day and centrifuged (11,000 rpm for 3 min at 4°C).

Total RNA was extracted from 2 ml of the cultured cell suspension using an E.Z.N.A. bacterial RNA kit (Omega). The amount and purity of the extracted RNA were determined using comparison of the optical density at 260 nm and the optical density at 280 nm and agarose gel electrophoresis to evaluate integrity. After digestion with DNase I, 2 μg of total RNA was reverse transcribed using a RevertAid first-strand cDNA synthesis kit (Thermo Scientific). Two pairs of specific primers (Table 1) were used to quantify the number of copies of the mlrA and the 16S rRNA genes, respectively. The RT-PCR commenced with 95°C for 2 min, followed by 45 cycles of 95°C for 15 s and 62°C for 45 s. The mRNA copy number was determined using the CT value. The gene expression ratio was calculated by the 2−ΔΔCT method according to the handbook for the Bio-Rad real-time PCR system, where ΔΔCT = (CT, target gene − CT, 16S rRNA)stress − (CT, target gene − CT, 16S rRNA)control. All assays were performed in triplicate, and analyses were conducted on means ± standard deviations (SDs). Analyses were conducted with Origin software (version 8.0; OriginLab).

RESULTS

Total Microcystis abundance and environmental parameters.

Several cyanobacterial blooms occurred in Dianchi Lake during the sampling period (Table 2). Total Microcystis abundance remained between 2.84 × 107 copies/liter and 5.29 × 108 copies/liter for all these blooms, while the water temperature remained between 10°C and 24°C. The total nitrogen content recorded during blooms varied from 1.833 mg/liter to 6.475 mg/liter, while the total phosphorus recorded varied from 0.196 mg/liter to 0.418 mg/liter.

TABLE 2.

Microcystis abundance and environmental parameters in Dianchi Lake from June 2010 to December 2011a

Sampling date (yr/mo/day) No. of Microcystis copies liter−1 Chla concn (μg/liter) Temp (°C) Concn (mg/liter)
TP TN SRP TDP
2010/06/19 1.12E+08 80.881 21.233 0.467 5.682 0.025 0.039
2010/07/16 1.04E+08 187.649 23.267 0.323 4.766 0.011 0.026
2010/08/17 1.45E+08 96.600 23.500 0.227 3.479 0.022 0.055
2010/09/15 4.74E+08 169.61 21.967 0.311 3.245 0.021 0.018
2010/10/16 2.28E+08 103.92 18.833 0.418 3.613 0.025 0.026
2010/11/19 3.27E+08 83.577 14.933 0.205 1.833 0.033 0.036
2010/12/16 2.40E+08 78.823 12.867 0.350 4.416 0.035 0.046
2011/01/14 1.10E+08 51.08 10.100 0.257 4.935 0.064 0.083
2011/02/19 2.84E+07 29.595 13.100 0.196 4.349 0.041 0.036
2011/03/18 4.22E+07 65.567 13.833 0.218 4.517 0.032 0.054
2011/04/20 4.52E+07 122.553 18.000 0.207 4.294 0.011 0.017
2011/05/18 5.92E+07 65.804 20.933 0.335 6.475 0.000 0.029
2011/06/23 1.93E+08 162.403 22.600 0.225 3.942 0.004 0.018
2011/07/22 1.68E+08 249.067 23.167 0.313 4.628 0.000 0.030
2011/08/17 1.47E+08 277.841 22.100 0.332 5.105 0.019 0.038
2011/09/20 5.29E+08 139.965 20.067 0.237 3.580 0.010 0.037
2011/10/14 2.30E+08 147.229 19.367 0.238 3.813 0.000 0.038
2011/11/21 3.49E+08 100.312 15.167 0.234 3.587 0.016 0.097
2011/12/15 5.29E+08 91.315 11.367 0.244 4.137 0.004 0.039
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a

Data are averages of three sampling sites. Chla, chlorophyll a; TP, total phosphorus; TN, total nitrogen; SRP, solubility-reactive phosphorus; TDP, total dissolved phosphorus.

Seasonal variation in abundance of total and toxic Microcystis spp.

Our results showed that large Microcystis blooms started from June to December and a peak occurred in September, while smaller Microcystis blooms occurred from February to April. Microcystis 16S rRNA gene copy numbers ranged from 1.54 × 106 copies/liter to 2.59 × 108 copies/liter at site D13, 4.62 × 106 copies/liter to 1.21 × 109 copies/liter at site D22, and 8.65 × 106 copies/liter to 1.27 ×109 copies/liter at site D24 (Fig. 2). Copy numbers of the mcyD gene revealed a trend similar to that seen for Microcystis spp. (5.34 × 105 copies/liter to 4.89 × 107 copies/liter at site D13, 2.74 × 106 copies/liter to 1.77 × 108 copies/liter at site D22, and 1.67 × 105 copies/liter to 2.22 × 107 copies/liter at site D24; Fig. 2). Meanwhile, we found that the proportions of toxic Microcystis were low from September through April but then increased from May to reach a maximum in June and July at all three sites (Fig. 2). These results indicate that cell numbers of both toxic Microcystis and total Microcystis exhibit similar trends during the entire period of the algal bloom, including the reinvasion, pelagic growth, sedimentation, and overwintering periods (27), and that the proportion of toxic Microcystis was highest during blooms and lowest in winter.

FIG 2.

FIG 2

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Seasonal variation in the abundance of total and toxic Microcystis spp. at each of the three sampling stations, D13 (a), D22 (b), and D24 (c), in Dianchi Lake from June 2010 to December 2011. The numbers of DNA copies were determined using qPCR. Error bars represent standard deviations. The toxic proportion was determined by dividing the relative number of copies of the mcyD gene by the total number of copies in Microcystis determined with the Microcystis 16S rRNA primer set.

Seasonal variation in the abundance of microcystins and MC-degrading bacteria.

Our results showed that at all three sampling sites, the MC concentration exhibited two distinct peaks in September 2010 and October 2011 (Fig. 3). Concentrations of MCs were higher in October 2011 than in September 2010 at two of the three sites (September 2010 concentrations were 1.33 μg/liter at site D13, 1.3 μg/liter at site D22, and 1.63 μg/liter at site D24; October 2011 concentrations were 1.421 μg/liter at site D13, 1.39 μg/liter at site D22, and 1.53 μg/liter at site D24) (Fig. 3).

FIG 3.

FIG 3

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Seasonal variation in the abundance of dissolved MCs and MC-degrading bacteria at each of the three sampling stations, D13 (a), D22 (b), and D24 (c), in Dianchi Lake from June 2010 to December 2011. The numbers of mlrA gene copies were determined using qPCR. Error bars represent standard deviations.

We found that mlrA gene copy numbers at site D13 ranged from 4.2 × 104 copies/liter to 3.49 × 108 copies/liter and exhibited two periods of increase: from June 2010 to October 2010 and from April 2011 to November 2011 (observations were not obtained for samples from December 2010 to March 2011, as copy numbers at this time were below the detection limit, i.e., <6.1 × 103 copies/liter) (Fig. 3). A similar pattern was observed at both sites D22 and D24, in which mlrA gene copy numbers ranged from 2.4 × 104 copies/liter to 4.44 × 107 copies/liter at site D22 and from 8.8 × 104 copies/liter to 9.62 × 107 copies/liter at site D24, with two periods of increase from June 2010 to October 2010 and from May 2011 to November 2011 (observations were not obtained for samples collected between January 2011 and April 2011 at these two sites). Peaks in the microcystin concentration were apparent in September 2010 and October 2011, while peaks in the mlrA gene copy numbers of MC-degrading bacteria appeared in the following months (October 2010 and November 2011).

Effects of MCs on mlrA gene expression.

Our results showed that the rate of MC degradation increased when MCs were added twice, suggesting that MC degradation activity is promoted by the intermittent addition of MC-LR and MC-RR to cultures of strain HW and strain SW (Fig. 4). We found that over 4 days, levels of expression of the strain HW mlrA gene increased 3.7 times under MC-LR stimulation and 5.2 times under MC-RR stimulation (Fig. 4). In contrast, the levels of expression of the strain SW mlrA gene increased marginally (Fig. 4).

FIG 4.

FIG 4

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Effect of MCs on mlrA gene expression. (a) Changes in MC concentrations with time (LR100 and RR100, MC-LR and MC-RR at 100 μg/liter, respectively); (b) changes in mlrA gene expression at different concentrations of MC-LR; (c) changes in mlrA gene expression at different concentrations of MC-RR.

DISCUSSION

Our analysis of the variation in the abundance of toxic Microcystis and MC-degrading bacterial communities in Dianchi Lake revealed that the cell numbers of Microcystis spp. and the mcyD gene varied in parallel, while the abundance of MC-degrading bacteria increased immediately after MC concentrations had reached their maximum. These findings suggest that the abundance of toxic Microcystis and microcystins in this lake affects the abundance of MC-degrading bacteria.

To analyze the seasonal dynamics of toxic Microcystis spp. and the MC-degrading bacterial community in field-collected water, TaqMan qPCR was used to quantify total Microcystis cell numbers, toxic Microcystis cell numbers, and MC-degrading bacterial abundance under the assumption that each M. aeruginosa PCC7806 cell has a constant copy number of the Microcystis 16S rRNA and mcyD genes. Previous studies have reported that Microcystis strains have one mcyD gene copy per genome (28), whereas genome sequencing analyses have found that a single Microcystis cell contains two copies of the rRNA gene cluster (29). Hence, the percentage of toxic Microcystis organisms is likely to be overestimated by qPCR. This problem has been discussed in detail by Rinta-Kanto et al. (8). Despite this possibility, our results nonetheless provide a snapshot of the relative dominance of the microcystin-producing strains within this lake community.

In Dianchi Lake, eutrophication has been evident since the late 1980s as a result of the escalating input of untreated wastewater and municipal sewage. This has resulted in dense Microcystis blooms (>108 cells liter−1 in summer) and microcystin contamination from April to November (30, 31). The results of this study reveal that the proportion of toxic Microcystis cells in the lake varied from 2.9% to 93.8% and was low from September to April and reached a maximum in June and July. We also were able to confirm that the largest Microcystis blooms always occurred from June to December (108 copies/liter to 109 copies/liter), while the smallest blooms occurred from February to April (106 copies/liter). This result is consistent with the findings of Davis et al. (32), who showed that eutrophication and climatic warming may act additively to promote the growth of toxic, rather than nontoxic, populations of Microcystis, leading to blooms with higher MC contents.

Several studies have shown that Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Bacteroidetes, Firmicutes, Deinococcus-Thermus, and Gemmatimonadetes are involved in the bacterial community diversity associated with Microcystis blooms (33–35). A GenBank and Ribosomal Database Project (RDP) analysis showed that the two MC-degrading bacteria (designated HW and SW) that we isolated were very similar to samples with the accession numbers AB161684.1 and JF833116, which belong to the class Alphaproteobacteria, order Sphingomonadales, family Sphingomonadaceae, genus Sphingopyxis. A number of molecular studies of bacterial communities associated with Microcystis blooms performed using targeted, 16S rRNA-type and metagenomic analyses have recently been reported. The use of targeted Sphingomonas showed that the Sphingomonadales seem to be an integral element of Microcystis blooms and can effectively degrade MCs as a result of their breakdown of the toxins (36). Comparison of the metagenomes of free-living bacterial plankton assemblages from Lake Erie in the United States showed that a diverse array of bacterial phyla was responsive to an elevated supply of MCs. This also included Sphingomonadales, although they were present at lower levels than other bacteria (37).

A key result of this study was that peaks in MC concentrations were followed (in the following months) by peaks in mlrA gene copy numbers of MC-degrading bacteria, which suggests that MCs released in field water may affect the MC-degrading bacterial communities in Dianchi Lake. Due to a sampling frequency of once per month, MC-degrading bacteria could potentially appear and again disappear in this time span. In addition, the concentrations of MCs in the lake also increased as the proportion of toxic Microcystis increased. These observations suggest that there is a strong association between the proportion of toxic Microcystis in the lake and the concentration of MCs and MC-degrading bacteria. Jones et al. (12) reported that, under experimental conditions, isolates of MC-degrading bacteria require a lag time to initiate degradation of MCs when they have not previously been exposed to MCs. Maruyama et al. (38), meanwhile, assumed that MC-degrading bacteria responded to changes in the concentration of MCs and began to degrade MCs as they were released from Microcystis cells. They speculated that MC-degrading bacteria in the mucilage remained on standby until the degradation of MCs occurred (i.e., they could be directly exposed to MCs released from cells in the water bloom). The findings of this study provide empirical support for these previous field study-based assumptions, demonstrating that seasonal variation in the abundance of MC-degrading bacteria in freshwater is related to the concentrations of both toxic Microcystis and MCs in the water.

These findings further suggest that MCs may act as sources of nutrition for MC-degrading bacteria. Previous studies proposed that MCs are used as secondary substrates by MC-degrading bacteria that come into contact with them (17, 22). Microorganisms accumulate in polysaccharide matrices and form structural and functional microbial assemblies on surfaces submerged in water commonly known as biofilms. Li et al. (39) found that the indigenous MC-degrading bacteria in biofilm can accumulate and become activated with MC-LR present, thereby increasing the efficiency with which MC degradation occurs. Furthermore, Li et al. (4) reported that mlrA gene abundance increased with increasing MC-LR concentrations, suggesting that biodegradation of MCs depends on the population of indigenous MC-degrading bacteria which primarily use MCs over other nutrients. In this study, we found that mlrA gene abundances increased under high concentrations of MCs, indicating that MC-degrading bacteria can use MCs for growth, without requiring other nutrients.

In conclusion, the data presented here show that large Microcystis blooms are correlated with a high abundance of toxic Microcystis, with concentrations of both microorganisms influencing the abundance of MC-degrading bacteria. These results suggest that toxic Microcystis and MC-degrading bacteria exert both indirect and direct effects on one another.

ACKNOWLEDGMENTS

This work was supported by grants from the National Natural Science Foundation of China (31370418), the Chinese Academy of Sciences (KSCX2-EW-Z-3), and the Natural Science Foundation of China-Yunnan Project (U0833604).

Footnotes

Published ahead of print 10 January 2014

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