Impacts of Multiwalled Carbon Nanotubes on Nutrient Removal from Wastewater and Bacterial Community Structure in Activated Sludge

<div><p>Background</p><p>The increasing use of multiwalled carbon nanotubes (MWCNTs) will inevitably lead to the exposure of wastewater treatment facilities. However, knowledge of the impacts of MWCNTs on wastewater nutrient removal and bacterial community structure in the activated sludge process is sparse.</p><p>Aims</p><p>To investigate the effects of MWCNTs on wastewater nutrient removal, and bacterial community structure in activated sludge.</p><p>Methods</p><p>Three triplicate sequencing batch reactors (SBR) were exposed to wastewater which contained 0, 1, and 20 mg/L MWCNTs. MiSeq sequencing was used to investigate the bacterial community structures in activated sludge samples which were exposed to different concentrations of MWCNTs.</p><p>Results</p><p>Exposure to 1 and 20 mg/L MWCNTs had no acute (1 day) impact on nutrient removal from wastewater. After long-term (180 days) exposure to 1 mg/L MWCNTs, the average total nitrogen (TN) removal efficiency was not significantly affected. TN removal efficiency decreased from 84.0% to 71.9% after long-term effects of 20 mg/L MWCNTs. After long-term exposure to 1 and 20 mg/L MWCNTs, the total phosphorus removal efficiencies decreased from 96.8% to 52.3% and from 98.2% to 34.0% respectively. Further study revealed that long-term exposure to 20 mg/L MWCNTs inhibited activities of ammonia monooxygenase and nitrite oxidoreductase. Long-term exposure to 1 and 20 mg/L MWCNTs both inhibited activities of exopolyphosphatase and polyphosphate kinase. MiSeq sequencing data indicated that 20 mg/L MWCNTs significantly decreased the diversity of bacterial community in activated sludge. Long-term exposure to 1 and 20 mg/L MWCNTs differentially decreased the abundance of nitrifying bacteria, especially ammonia-oxidizing bacteria. The abundance of PAOs was decreased after long-term exposure to 20 mg/L MWCNTs. The abundance of glycogen accumulating organisms (GAOs) was increased after long-term exposure to 1 mg/L MWCNTs.</p><p>Conclusion</p><p>MWCNTs have adverse effects on biological wastewater nutrient removal, and altered the diversity and structure of bacterial community in activated sludge.</p></div

Bacterial Community Dynamics and Taxa-Time Relationships within Two Activated Sludge Bioreactors

<div><p>Background</p><p>Biological activated sludge process must be functionally stable to continuously remove contaminants while relying upon the activity of complex microbial communities. However the dynamics of these communities are as yet poorly understood. A macroecology metric used to quantify community dynamic is the taxa-time relationship (TTR). Although the TTR of animal and plant species has been well documented, knowledge is still lacking in regard to TTR of microbial communities in activated sludge bioreactors.</p><p>Aims</p><p>1) To characterize the temporal dynamics of bacterial taxa in activated sludge from two bioreactors of different scale and investigate factors affecting such dynamics; 2) to evaluate the TTRs of activated sludge microbial communities in two bioreactors of different scale.</p><p>Methods</p><p>Temporal variation of bacterial taxa in activated sludge collected from a full- and lab-scale activated sludge bioreactor was monitored over a one-year period using pyrosequencing of 16S rRNA genes. TTR was employed to quantify the bacterial taxa shifts based on the power law equation <i>S = cT^w</i>.</p><p>Results</p><p>The power law exponent <i>w</i> for the full-scale bioreactor was 0.43 (<i>R²</i> = 0.970), which is lower than that of the lab-scale bioreactor (<i>w</i> = 0.55, <i>R²</i> = 0.971). The exponents for the dominant phyla were generally higher than that of the rare phyla. Canonical correspondence analysis (CCA) result showed that the bacterial community variance was significantly associated with water temperature, influent (biochemical oxygen demand) BOD, bioreactor scale and dissolved oxygen (DO). Variance partitioning analyses suggested that wastewater characteristics had the greatest contribution to the bacterial community variance, explaining 20.3% of the variance of bacterial communities independently, followed by operational parameters (19.9%) and bioreactor scale (3.6%).</p><p>Conclusions</p><p>Results of this study suggest bacterial community dynamics were likely driven partly by wastewater and operational parameters and provide evidence that the TTR may be a fundamental ecological pattern in macro- and microbial systems.</p></div

Number of taxa classified by different taxonomic levels from the full-and lab-scale bioreactor.

a<p>Full-scale bioreactor.</p>b<p>Lab-scale bioreactor.</p

Heat map of top 10 genera in each sample.

<p>Total 36 genera were selected from nine samples, and the color intensity in each panel shows the percentage of a genus in a sample, referring to color key at the right side.</p

Canonical correspondence analysis (CCA) of pyrosequencing data and measurable variables in a full- and lab-scale bioreactors.

<p>Arrows indicate the direction and magnitude of measurable variables associated with bacterial community structures. Circles and triangles represent different bacterial community structures from the full- and lab-scale bioreactor, respectively. Samples are named with “F” (Full-scale bioreactor) or “L” (Lab-scale bioreactor) and numbers. Sample numbers: 1- May 2010, 2- June 2010, 3-July 2010, 4- August 2010, 5-September 2010, 6- October 2010, 7-November 2010, 8-December 2010, 9-January 2011, 10- February 2011, 11-March 2011, 12-April 2011.</p

Taxa-time relationships for a full-scale bioreactor (circles) and lab-scale bioreactor (triangles).

<p>The lines are fitted to a power law equation <i>S</i> = <i>cT^w</i>, where <i>S</i> is the number of observed taxa, <i>c</i> is the constant, <i>T</i> is the time, and <i>w</i> is the taxa-time relationship exponent.</p

Relationship between operation parameters and bacterial community structure in nine samples.

a<p><i>r_M</i>, Mantels correlation coefficient.</p><p>Relationship between operation parameters and bacterial community structure in nine samples.</p

Abundances of different phyla and classes in <i>Proteobacteria</i> in the nine activated sludge samples.

<p>The abundance is presented in terms of percentage in total effective bacterial sequences in a sample.</p

Bacterial diversity indices of nine activated sludge samples from three sequencing batch reactors (3% cutoff).

<p>Bacterial diversity indices of nine activated sludge samples from three sequencing batch reactors (3% cutoff).</p

The power law exponent of taxa-time relationship for each phylum within two activated sludge bioreactors.

a<p>It is an average of the relative abundance of each phylum within 12 samples.</p