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This study aimed to determine if biotic contaminants originating from pig production farms are disseminated into soil and groundwater microbial communities. A spatial and temporal sampling of soil and groundwater in proximity to pig production farms was conducted, and quantitative PCR (Q-PCR) was utilized to determine the abundances of tetracycline resistance genes (i.e., tetQ and tetZ ) and integrase genes (i.e., intI1 and intI2 ). We observed that the abundances of tetZ , tetQ , intI1 , and intI2 in the soils increased at least 6-fold after manure application, and their abundances remained elevated above the background for up to 16 months. Q-PCR further determined total abundances of up to 5.88 × 10 9 copies/ng DNA for tetZ , tetQ , intI1 , and intI2 in some of the groundwater wells that were situated next to the manure lagoon and in the facility well used to supply water for one of the farms. We further utilized 16S rRNA-based pyrosequencing to assess the microbial communities, and our comparative analyses suggest that most of the soil samples collected before and after manure application did not change significantly, sharing a high Bray-Curtis similarity of 78.5%. In contrast, an increase in Bacteroidetes and sulfur-oxidizing bacterial populations was observed in the groundwaters collected from lagoon-associated groundwater wells. Genera associated with opportunistic human and animal pathogens, such as Acinetobacter , Arcobacter , Yersinia , and Coxiella , were detected in some of the manure-treated soils and affected groundwater wells. Feces-associated bacteria such as Streptococcus , Erysipelothrix , and Bacteroides were detected in the manure, soil, and groundwater ecosystems, suggesting a perturbation of the soil and groundwater environments by invader species from pig production activities.

In this study, we evaluated the specificity, distribution, and sensitivity of Prevotella strain-based (PF163 and PigBac1) and methanogen-based (P23-2) PCR assays proposed to detect swine fecal pollution in environmental waters. The assays were tested against 222 fecal DNA extracts derived from target and nontarget animal hosts and against 34 groundwater and 15 surface water samples from five different sites. We also investigated the phylogenetic diversity of 1,340 “ Bacteroidales ” 16S rRNA gene sequences derived from swine feces, swine waste lagoons, swine manure pits, and waters adjacent to swine operations. Most swine fecal samples were positive for the host-specific Prevotella- based PCR assays (80 to 87%), while fewer were positive with the methanogen-targeted PCR assay (53%). Similarly, the Prevotella markers were detected more frequently than the methanogen-targeted assay markers in waters historically impacted with swine fecal contamination. However, the PF163 PCR assay cross-reacted with 23% of nontarget fecal DNA extracts, although Bayesian statistics suggested that it yielded the highest probability of detecting pig fecal contamination in a given water sample. Phylogenetic analyses revealed previously unknown swine-associated clades comprised of clones from geographically diverse swine sources and from water samples adjacent to swine operations that are not targeted by the Prevotella assays. While deeper sequencing coverage might be necessary to better understand the molecular diversity of fecal Bacteroidales species, results of sequence analyses supported the presence of swine fecal pollution in the studied watersheds. Overall, due to nontarget cross amplification and poor geographic stability of currently available host-specific PCR assays, development of additional assays is necessary to accurately detect sources of swine fecal pollution.

To monitor the dissemination of resistance genes into the environment, we determined the occurrence of tetracycline resistance (Tc r ) genes in groundwater underlying two swine confinement operations. Monitoring well networks (16 wells at site A and 6 wells at site C) were established around the lagoons at each facility. Groundwater ( n = 124) and lagoon ( n = 12) samples were collected from the two sites at six sampling times from 2000 through 2003. Total DNA was extracted, and PCR was used to detect seven Tc r genes [ tet (M), tet (O), tet (Q), tet (W), tet (C), tet (H), and tet (Z)]. The concentration of Tc r genes was quantified by real-time quantitative PCR. To confirm the Tc r gene source in groundwater, comparative analysis of tet (W) gene sequences was performed on groundwater and lagoon samples. All seven Tc r genes were continually detected in groundwater during the 3-year monitoring period at both sites. At site A, elevated detection frequency and concentration of Tc r genes were observed in the wells located down-gradient of the lagoon. Comparative analysis of tet (W) sequences revealed that the impacted groundwater contained gene sequences almost identical (99.8% identity) to those in the lagoon, but these genes were not found in background libraries. Novel sequence clusters and unique indigenous resistance gene pools were also found in the groundwater. Thus, antibiotic resistance genes in groundwater are affected by swine manure, but they are also part of the indigenous gene pool.

Examination of variation in ecological communities can lead to an understanding of the forces that structure communities, the consequences of change at the ecosystem level, and the relevant scales involved. This study details spatial and seasonal variability in the composition of nitrogen-fixing and cyanobacterial (i.e., oxygenic photosynthetic) functional groups of a benthic, hypersaline microbial mat from Salt Pond, San Salvador Island, Bahamas. This system shows extreme annual variability in the salinity of the overlying water and the extent of water coverage. Analysis of molecular variance and F ST tests of genetic differentiation of nifH and cyanobacterial 16S rRNA gene clone libraries allowed for changes at multiple taxonomic levels (i.e., above, below, and at the species level) to inform the conclusions regarding these functional groups. Composition of the nitrogen-fixing community showed significant seasonal changes related to salinity, while cyanobacterial composition showed no consistent seasonal pattern. Both functional groups exhibited significant spatial variation, changing with depth in the mat and horizontally with distance from the shoreline. The patterns of change suggest that cyanobacterial composition was more insensitive to water stress, and consequently, cyanobacteria dominated the nitrogen-fixing community during dry months but gave way to a more diverse community of diazotrophs in wet months. This seasonal pattern may allow the mat community to respond quickly to water-freshening events after prolonged dry conditions (system recovery) and maintain ecosystem function in the face of disturbance during the wet season (system resilience).

This study used a genetic fingerprinting technique (automated ribosomal intergenic spacer analysis [ARISA]) to characterize microbial communities from a culture-independent perspective and to identify those environmental factors that influence the diversity of bacterial assemblages in Wisconsin lakes. The relationships between bacterial community composition and 11 environmental variables for a suite of 30 lakes from northern and southern Wisconsin were explored by canonical correspondence analysis (CCA). In addition, the study assessed the influences of ARISA fragment detection threshold (sensitivity) and the quantitative, semiquantitative, and binary (presence-absence) use of ARISA data. It was determined that the sensitivity of ARISA was influential only when presence-absence-transformed data were used. The outcomes of analyses depended somewhat on the data transformation applied to ARISA data, but there were some features common to all of the CCA models. These commonalities indicated that differences in bacterial communities were best explained by regional (i.e., northern versus southern Wisconsin lakes) and landscape level (i.e., seepage lakes versus drainage lakes) factors. ARISA profiles from May samples were consistently different from those collected in other months. In addition, communities varied along gradients of pH and water clarity (Secchi depth) both within and among regions. The results demonstrate that environmental, temporal, regional, and landscape level features interact to determine the makeup of bacterial assemblages in northern temperate lakes.