Determining Hot Spots of Fecal Contamination in a Tropical Watershed by Combining Land-Use Information and Meteorological Data with Source-Specific Assays

The objective of this study was to combine knowledge of environmental, topographical, meteorological, and anthropologic factors in the Río Grande de Arecibo (RGA) watershed in Puerto Rico with information provided by microbial source tracking (MST) to map hot spots (i.e., likely sources) of fecal contamination. Water samples were tested for the presence of human and bovine fecal contamination in addition to fecal indicator bacteria and correlated against several land uses and the density of septic tanks, sewers, and latrines. Specifically, human sources were positively correlated with developed (<i>r</i> = 0.68), barren land uses (<i>r</i> = 0.84), density of septic tanks (<i>r</i> = 0.78), slope (<i>r</i> = 0.63), and the proximity to wastewater treatment plants (WWTPs) (<i>r</i> = 0.82). Agricultural land, the number of upstream National Pollution Discharge Elimination System (NPDES) facilities, and density of latrines were positively associated with the bovine marker (<i>r</i> = 0.71; <i>r</i> = 0.74; and <i>r</i> = 0.68, respectively). Using this information, we provided a hot spot map, which shows areas that should be closely monitored for fecal contamination in the RGA watershed. The results indicated that additional bovine assays are needed in tropical regions. We concluded that meteorological, topographical, anthropogenic, and land cover data are needed to evaluate and verify the performance of MST assays and, therefore, to identify important sources of fecal contamination in environmental waters

Detection of Fecal Bacteria and Source Tracking Identifiers in Environmental Waters Using rRNA-Based RT-qPCR and rDNA-Based qPCR Assays

In this study, we evaluated the use of RT-qPCR assays targeting rRNA gene sequences for the detection of fecal bacteria in water samples. We challenged the RT-qPCR assays against RNA extracted from sewage effluent (<i>n</i> = 14), surface water (<i>n</i> = 30), and treated source water (<i>n</i> = 15) samples. Additionally, we applied the same assays using DNA as the qPCR template. The targeted fecal bacteria were present in most of the samples tested, although in several cases, the detection frequency increased when RNA was used as the template. For example, the majority of samples that tested positive for <i>E. coli</i> and <i>Campylobacter</i> spp. in surface waters, and for human-specific <i>Bacteroidales</i>, <i>E. coli</i>, and <i>Enterococcus</i> spp. in treated source waters were only detected when rRNA was used as the original template. The difference in detection frequency using rRNA or rDNA (rRNA gene) was sample- and assay-dependent, suggesting that the abundance of active and nonactive populations differed between samples. Statistical analyses for each population exhibiting multiple quantifiable results showed that the rRNA copy numbers were significantly higher than the rDNA counterparts (<i>p</i> < 0.05). Moreover, the detection frequency of rRNA-based assays were in better agreement with the culture-based results of <i>E. coli</i>, intestinal enterococci, and thermotolerant <i>Campylobacter</i> spp. in surface waters than that of rDNA-based assays, suggesting that rRNA signals were associated to active bacterial populations. Our data show that using rRNA-based approaches significantly increases detection sensitivity for common fecal bacteria in environmental waters. These findings have important implications for microbial water quality monitoring and public health risk assessments

Detection of Fecal Bacteria and Source Tracking Identifiers in Environmental Waters Using rRNA-Based RT-qPCR and rDNA-Based qPCR Assays

In this study, we evaluated the use of RT-qPCR assays targeting rRNA gene sequences for the detection of fecal bacteria in water samples. We challenged the RT-qPCR assays against RNA extracted from sewage effluent (<i>n</i> = 14), surface water (<i>n</i> = 30), and treated source water (<i>n</i> = 15) samples. Additionally, we applied the same assays using DNA as the qPCR template. The targeted fecal bacteria were present in most of the samples tested, although in several cases, the detection frequency increased when RNA was used as the template. For example, the majority of samples that tested positive for <i>E. coli</i> and <i>Campylobacter</i> spp. in surface waters, and for human-specific <i>Bacteroidales</i>, <i>E. coli</i>, and <i>Enterococcus</i> spp. in treated source waters were only detected when rRNA was used as the original template. The difference in detection frequency using rRNA or rDNA (rRNA gene) was sample- and assay-dependent, suggesting that the abundance of active and nonactive populations differed between samples. Statistical analyses for each population exhibiting multiple quantifiable results showed that the rRNA copy numbers were significantly higher than the rDNA counterparts (<i>p</i> < 0.05). Moreover, the detection frequency of rRNA-based assays were in better agreement with the culture-based results of <i>E. coli</i>, intestinal enterococci, and thermotolerant <i>Campylobacter</i> spp. in surface waters than that of rDNA-based assays, suggesting that rRNA signals were associated to active bacterial populations. Our data show that using rRNA-based approaches significantly increases detection sensitivity for common fecal bacteria in environmental waters. These findings have important implications for microbial water quality monitoring and public health risk assessments

Detection of Fecal Bacteria and Source Tracking Identifiers in Environmental Waters Using rRNA-Based RT-qPCR and rDNA-Based qPCR Assays

In this study, we evaluated the use of RT-qPCR assays targeting rRNA gene sequences for the detection of fecal bacteria in water samples. We challenged the RT-qPCR assays against RNA extracted from sewage effluent (<i>n</i> = 14), surface water (<i>n</i> = 30), and treated source water (<i>n</i> = 15) samples. Additionally, we applied the same assays using DNA as the qPCR template. The targeted fecal bacteria were present in most of the samples tested, although in several cases, the detection frequency increased when RNA was used as the template. For example, the majority of samples that tested positive for <i>E. coli</i> and <i>Campylobacter</i> spp. in surface waters, and for human-specific <i>Bacteroidales</i>, <i>E. coli</i>, and <i>Enterococcus</i> spp. in treated source waters were only detected when rRNA was used as the original template. The difference in detection frequency using rRNA or rDNA (rRNA gene) was sample- and assay-dependent, suggesting that the abundance of active and nonactive populations differed between samples. Statistical analyses for each population exhibiting multiple quantifiable results showed that the rRNA copy numbers were significantly higher than the rDNA counterparts (<i>p</i> < 0.05). Moreover, the detection frequency of rRNA-based assays were in better agreement with the culture-based results of <i>E. coli</i>, intestinal enterococci, and thermotolerant <i>Campylobacter</i> spp. in surface waters than that of rDNA-based assays, suggesting that rRNA signals were associated to active bacterial populations. Our data show that using rRNA-based approaches significantly increases detection sensitivity for common fecal bacteria in environmental waters. These findings have important implications for microbial water quality monitoring and public health risk assessments

The Roles of Biofilm Conductivity and Donor Substrate Kinetics in a Mixed-Culture Biofilm Anode

We experimentally assessed the kinetics and thermodynamics of electron transfer (ET) from the donor substrate (acetate) to the anode for a mixed-culture biofilm anode. We interpreted the results with a modified biofilm-conduction model consisting of three ET steps in series: (1) intracellular ET, (2) non-Ohmic extracellular ET (EET) from an outer membrane protein to an extracellular cofactor (EC), and (3) ET from the EC to the anode by Ohmic-conduction in the biofilm matrix. The steady-state current density was 0.82 ± 0.03 A/m² in a miniature microbial electrochemical cell operated at fixed anode potential of −0.15 V versus the standard hydrogen electrode. Illumina 16S-rDNA and -rRNA sequences showed that the <i>Geobacter</i> genus was less than 30% of the community of the biofilm anode. Biofilm conductivity was high at 2.44 ± 0.42 mS/cm, indicating that the maximum current density could be as high as 270 A/m² if only Ohmic-conduction EET was limiting. Due to the high biofilm conductivity, the maximum energy loss for Ohmic-conduction EET was negligible, 0.085 mV. The energy loss in the second ET step also was small, only 20 mV, and the potential for the EC involved in the second ET was −0.15 V, a value documenting that >99% of the EC was in the oxidized state. Monod kinetics for utilization of acetate were relatively slow, and at least 87% of the energy loss was in the intracellular step. Thus, intracellular ET was the main kinetic and thermodynamic bottleneck to ET from donor substrate to the anode for a highly conductive biofilm

Microbial Community Response to Chlorine Conversion in a Chloraminated Drinking Water Distribution System

Temporary conversion to chlorine (i.e., “chlorine burn”) is a common approach to controlling nitrification in chloraminated drinking water distribution systems, yet its effectiveness and mode(s) of action are not fully understood. This study characterized occurrence of nitrifying populations before, during and after a chlorine burn at 46 sites in a chloraminated distribution system with varying pipe materials and levels of observed nitrification. Quantitative polymerase chain reaction analysis of gene markers present in nitrifying populations indicated higher frequency of detection of ammonia oxidizing bacteria (AOB) (72% of samples) relative to ammonia oxidizing archaea (AOA) (28% of samples). <i>Nitrospira</i> nitrite oxidizing bacteria (NOB) were detected at 45% of samples, while presence of <i>Nitrobacter</i> NOB could not be confirmed at any of the samples. During the chlorine burn, the numbers of AOA, AOB, and <i>Nitrospira</i> greatly reduced (i.e., 0.8–2.4 log). However, rapid and continued regrowth of AOB and <i>Nitrospira</i> were observed along with nitrite production in the bulk water within four months after the chlorine burn, and nitrification outbreaks appeared to worsen 6–12 months later, even after adopting a twice annual burn program. Although high throughput sequencing of 16S rRNA genes revealed a distinct community shift and higher diversity index during the chlorine burn, it steadily returned towards a condition more similar to pre-burn than burn stage. Significant factors associated with nitrifier and microbial community composition included water age and sampling location type, but not pipe material. Overall, these results indicate that there is limited long-term effect of chlorine burns on nitrifying populations and the broader microbial community

The Impact of Silver Nanoparticles on the Composting of Municipal Solid Waste

The study evaluates the impact of polyvinylpyrrolidone (PVP) coated silver nanoparticles (PVP-AgNPs) on the composting of municipal solid waste. The results suggest that there was no statistically significant difference in the leachate, gas, and solid quality parameters and overall composting performance between the treatments containing the AgNPs, Ag⁺, and negative control. Nonetheless, taxonomical analyses of 25 Illumina 16S rDNA barcoded libraries containing 2 393 504 sequences indicated that the bacterial communities in composted samples were highly diverse and primarily dominated by Clostridia (48.5%), Bacilli (27.9%), and beta-Proteobacteria (13.4%). Bacterial diversity studies showed that the overall bacterial community structure in the composters changed in response to the Ag-based treatments. However, the data suggest that functional performance was not significantly affected due to potential bacterial functional redundancy within the compost samples. The data also indicate that while the surface transformation of AgNPs to AgCl and Ag₂S can reduce the toxicity, complexation with organic matter may also play a major role. The results of this study further suggest that at relatively low concentrations, the organically rich waste management systems’ functionality may not be influenced by the presence of AgNPs

Dramatic Improvements in Beach Water Quality Following Gull Removal

Gulls are often cited as important contributors of fecal contamination to surface waters, and some recreational beaches have used gull control measures to improve microbial water quality. In this study, gulls were chased from a Lake Michigan beach using specially trained dogs, and water quality improvements were quantified. Fecal indicator bacteria and potentially pathogenic bacteria were measured before and during gull control using culture methods and quantitative polymerase chain reaction (qPCR). Harassment by dogs was an effective method of gull control: average daily gull populations fell from 665 before to 17 during intervention; and a significant reduction in the density of a gull-associated marker was observed (<i>p</i> < 0.001). <i>Enterococcus</i> spp. and <i>Escherichia coli</i> densities were also significantly reduced during gull control (<i>p</i> < 0.001 and <i>p</i> = 0.012, respectively for culture methods; <i>p</i> = 0.012 and <i>p</i> = 0.034, respectively for qPCR). Linear regression results indicate that a 50% reduction in gulls was associated with a 38% and 29% decrease in <i>Enterococcus</i> spp. and <i>E. coli</i> densities, respectively. Potentially human pathogenic bacteria were detected on 64% of days prior to gull control and absent during gull intervention, a significant reduction (<i>p</i> = 0.005). This study demonstrates that gull removal can be a highly successful beach remedial action to improve microbial water quality

Categorized distance and proportion of cases within those groups in a waterborne outbreak in Vuorela, July 2012.

<p>Categorized distance and proportion of cases within those groups in a waterborne outbreak in Vuorela, July 2012.</p

The Univariate and multivariate results for individual risk factors and the generalized additive model risk ratios with the spatial term of a waterborne outbreak in Vuorela, July 2012.

<p>The Univariate and multivariate results for individual risk factors and the generalized additive model risk ratios with the spatial term of a waterborne outbreak in Vuorela, July 2012.</p