Tertiary-Treated Municipal Wastewater is a Significant Point Source of Antibiotic Resistance Genes Into Duluth-Superior Harbor

In this study, the impact of tertiary-treated municipal wastewater on the quantity of several antibiotic resistance determinants in Duluth-Superior Harbor was investigated by collecting surface water and sediment samples from 13 locations in Duluth-Superior Harbor, the St. Louis River, and Lake Superior. Quantitative PCR (qPCR) was used to target three different genes encoding resistance to tetracycline (tet(A), tet(X), and tet(W)), the gene encoding the integrase of class 1 integrons (intI1), and total bacterial abundance (16S rRNA genes) as well as total and human fecal contamination levels (16S rRNA genes specific to the genus Bacteroides). The quantities of tet(A), tet(X), tet(W), intI1, total Bacteroides, and human-specific Bacteroides were typically 20-fold higher in the tertiary-treated wastewater than in nearby surface water samples. In contrast, the quantities of these genes in the St. Louis River and Lake Superior were typically below detection. Analysis of sequences of tet(W) gene fragments from four different samples collected throughout the study site supported the conclusion that tertiary-treated municipal wastewater is a point source of resistance genes into Duluth-Superior Harbor. This study demonstrates that the discharge of exceptionally treated municipal wastewater can have a statistically significant effect on the quantities of antibiotic resistance genes in otherwise pristine surface waters

Characterization and quantification of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in a nitrogen-removing reactor using T-RFLP and qPCR

Using ammonia monooxygenase α-subunit (amoA) gene and 16S rRNA gene, the community structure and abundance of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in a nitrogen-removing reactor, which was operated for five phases, were characterized and quantified by cloning, terminal restriction fragment length polymorphism (T-RFLP), and quantitative polymerase chain reaction (qPCR). The results suggested that the dominant AOB in the reactor fell to the genus Nitrosomonas, while the dominant AOA belonged to Crenarchaeotal Group I.1a in phylum Crenarchaeota. Real-time PCR results demonstrated that the levels of AOB amoA varied from 2.9 × 103 to 2.3 × 105 copies per nanogram DNA, greatly (about 60 times) higher than those of AOA, which ranged from 1.7 × 102 to 3.8 × 103 copies per nanogram DNA. This indicated the possible leading role of AOB in the nitrification process in this study. T-RFLP results showed that the AOB community structure significantly shifted in different phases while AOA only showed one major peak for all the phases. The analyses also suggested that the AOB community was more sensitive than that of AOA to operational conditions, such as ammonia loading and dissolved oxygen

Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators

BACKGROUND: Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. METHODOLOGY/PRINCIPAL FINDINGS: Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and alpha-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC:A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. CONCLUSIONS/SIGNIFICANCE: This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health

Metabolic and Genetic Diversity of Mesophilic and Thermophilic Bacteria Isolated from Composted Municipal Sludge on Poly-e-caprolactones

Thirty mesophilic and thermophilic bacteria were isolated from thermobiotically digested sewage sludge in culture medium supplemented with poly-e-caprolactone (PCL). The ability of each purified isolate to degrade PCL and to produce polymer-degrading extracellular enzymes was assessed. Isolates were characterized based on random amplified polymorphic DNA (RAPD), 16S rDNA sequence-based phylogenetic affiliation and carbohydrate-based nutritional versatility. Mesophilic isolates with ability to degrade PCL were attributed to the genera Acinetobacter, Burkholderia, Pseudomonas, and Staphylococcus. Thermophilic isolates were members of the genus Bacillus. Despite the restricted phylogenetic and genotypic diversity observed for thermophiles, their metabolic versatility and wide range of growth temperatures suggest an important activity of these organisms during the whole composting process

Bacterial community structures are unique and resilient in full-scale bioenergy systems

Anaerobic digestion is the most successful bioenergy technology worldwide with, at its core, undefined microbial communities that have poorly understood dynamics. Here, we investigated the relationships of bacterial community structure (>400,000 16S rRNA gene sequences for 112 samples) with function (i.e., bioreactor performance) and environment (i.e., operating conditions) in a yearlong monthly time series of nine full-scale bioreactor facilities treating brewery wastewater (>20,000 measurements). Each of the nine facilities had a unique community structure with an unprecedented level of stability. Using machine learning, we identified a small subset of operational taxonomic units (OTUs; 145 out of 4,962), which predicted the location of the facility of origin for almost every sample (96.4% accuracy). Of these 145 OTUs, syntrophic bacteria were systematically overrepresented, demonstrating that syntrophs rebounded following disturbances. This indicates that resilience, rather than dynamic competition, played an important role in maintaining the necessary syntrophic populations. In addition, we explained the observed phylogenetic differences between all samples on the basis of a subset of environmental gradients (using constrained ordination) and found stronger relationships between community structure and its function rather than its environment. These relationships were strongest for two performance variables—methanogenic activity and substrate removal efficiency—both of which were also affected by microbial ecology because these variables were correlated with community evenness (at any given time) and variability in phylogenetic structure (over time), respectively. Thus, we quantified relationships between community structure and function, which opens the door to engineer communities with superior functions