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Estimating cyanobacteria community dynamics and its relationship with environmental factors.

Luo W, Chen H, Lei A, Lu J, Hu Z - Int J Environ Res Public Health (2014)

Bottom Line: The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 10(8) cells L(-1) and 1.92 × 10(8) cells L(-1) in the Tiegang and Shiyan reservoirs, respectively.Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors.The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen.

View Article: PubMed Central - PubMed

Affiliation: Shenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory of Marine Algal Biotechnology, College of Life Science, Shenzhen University, Shenzhen 518060, China. luowh127@gmail.com.

ABSTRACT
The cyanobacteria community dynamics in two eutrophic freshwater bodies (Tiegang Reservoir and Shiyan Reservoir) was studied with both a traditional microscopic counting method and a PCR-DGGE genotyping method. Results showed that cyanobacterium Phormidium tenue was the predominant species; twenty-six cyanobacteria species were identified in water samples collected from the two reservoirs, among which fourteen were identified with the morphological method and sixteen with the PCR-DGGE method. The cyanobacteria community composition analysis showed a seasonal fluctuation from July to December. The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 10(8) cells L(-1) and 1.92 × 10(8) cells L(-1) in the Tiegang and Shiyan reservoirs, respectively. Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors. The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen. This study demonstrated that data obtained from PCR-DGGE combined with a traditional morphological method could reflect cyanobacteria community dynamics and its correlation with environmental factors in eutrophic freshwater bodies.

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The cyanobacteria community structure system tree map of Tiegang and Shiyan reservoir water samples from July to December in 2007. T7–T12: Samples from July to December in Tiegang Reservoir; S7–S12: Samples from July to December in Shiyan Reservoir. The purpose of the tree is to show the clades.
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ijerph-11-01141-f003: The cyanobacteria community structure system tree map of Tiegang and Shiyan reservoir water samples from July to December in 2007. T7–T12: Samples from July to December in Tiegang Reservoir; S7–S12: Samples from July to December in Shiyan Reservoir. The purpose of the tree is to show the clades.

Mentions: Band numbers of DGGE products were compared among samples using Quantity One (Bio-Rad). T10 was designated as the standard for relative quantification. Bands at the same position were considered as the same species. The relative biomass was represented by the DNA amounts from the bands. The Cs (Dice coefficient) correlation between relative biomass of each band ranged from 38.1% (T8 and S12) to 78.8% (T11 and S11), which means cyanobacteria community in December of Shiyan and August of Tiegang were mostly different, while the two reservoirs had similar cyanobacteria communities in November. Based on similarity analysis, results were converted into UPGMA diagram (Figure 3) using Quantity One. The tree had three major clades. Clade I consisted of cyanobacteria species in August and September (Lanes T8, S8, T9 and S9). Clade II consisted of cyanobacteria species in November (Lanes T11, S11). Clade III consisted of samples collected in December (Lanes T12, S12), October and July (Lanes T7, S10, S7, and T10). Overall, the cyanobacteria community structure was very similar between the two reservoirs in the same month while it showed seasonal changes in the same reservoir.


Estimating cyanobacteria community dynamics and its relationship with environmental factors.

Luo W, Chen H, Lei A, Lu J, Hu Z - Int J Environ Res Public Health (2014)

The cyanobacteria community structure system tree map of Tiegang and Shiyan reservoir water samples from July to December in 2007. T7–T12: Samples from July to December in Tiegang Reservoir; S7–S12: Samples from July to December in Shiyan Reservoir. The purpose of the tree is to show the clades.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3924496&req=5

ijerph-11-01141-f003: The cyanobacteria community structure system tree map of Tiegang and Shiyan reservoir water samples from July to December in 2007. T7–T12: Samples from July to December in Tiegang Reservoir; S7–S12: Samples from July to December in Shiyan Reservoir. The purpose of the tree is to show the clades.
Mentions: Band numbers of DGGE products were compared among samples using Quantity One (Bio-Rad). T10 was designated as the standard for relative quantification. Bands at the same position were considered as the same species. The relative biomass was represented by the DNA amounts from the bands. The Cs (Dice coefficient) correlation between relative biomass of each band ranged from 38.1% (T8 and S12) to 78.8% (T11 and S11), which means cyanobacteria community in December of Shiyan and August of Tiegang were mostly different, while the two reservoirs had similar cyanobacteria communities in November. Based on similarity analysis, results were converted into UPGMA diagram (Figure 3) using Quantity One. The tree had three major clades. Clade I consisted of cyanobacteria species in August and September (Lanes T8, S8, T9 and S9). Clade II consisted of cyanobacteria species in November (Lanes T11, S11). Clade III consisted of samples collected in December (Lanes T12, S12), October and July (Lanes T7, S10, S7, and T10). Overall, the cyanobacteria community structure was very similar between the two reservoirs in the same month while it showed seasonal changes in the same reservoir.

Bottom Line: The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 10(8) cells L(-1) and 1.92 × 10(8) cells L(-1) in the Tiegang and Shiyan reservoirs, respectively.Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors.The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen.

View Article: PubMed Central - PubMed

Affiliation: Shenzhen Key Laboratory of Marine Bioresource and Eco-environmental Science, Shenzhen Engineering Laboratory of Marine Algal Biotechnology, College of Life Science, Shenzhen University, Shenzhen 518060, China. luowh127@gmail.com.

ABSTRACT
The cyanobacteria community dynamics in two eutrophic freshwater bodies (Tiegang Reservoir and Shiyan Reservoir) was studied with both a traditional microscopic counting method and a PCR-DGGE genotyping method. Results showed that cyanobacterium Phormidium tenue was the predominant species; twenty-six cyanobacteria species were identified in water samples collected from the two reservoirs, among which fourteen were identified with the morphological method and sixteen with the PCR-DGGE method. The cyanobacteria community composition analysis showed a seasonal fluctuation from July to December. The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 10(8) cells L(-1) and 1.92 × 10(8) cells L(-1) in the Tiegang and Shiyan reservoirs, respectively. Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors. The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen. This study demonstrated that data obtained from PCR-DGGE combined with a traditional morphological method could reflect cyanobacteria community dynamics and its correlation with environmental factors in eutrophic freshwater bodies.

Show MeSH
Related in: MedlinePlus