Global Distribution of Human-Associated Fecal Genetic Markers in Reference Samples from Six Continents.

Numerous bacterial genetic markers are available for the molecular detection of human sources of fecal pollution in environmental waters. However, widespread application is hindered by a lack of knowledge regarding geographical stability, limiting implementation to a small number of well-characterized regions. This study investigates the geographic distribution of five human-associated genetic markers (HF183/BFDrev, HF183/BacR287, BacHum-UCD, BacH, and Lachno2) in municipal wastewaters (raw and treated) from 29 urban and rural wastewater treatment plants (750-4 400 000 population equivalents) from 13 countries spanning six continents. In addition, genetic markers were tested against 280 human and nonhuman fecal samples from domesticated, agricultural and wild animal sources. Findings revealed that all genetic markers are present in consistently high concentrations in raw (median log10 7.2-8.0 marker equivalents (ME) 100 mL-1) and biologically treated wastewater samples (median log10 4.6-6.0 ME 100 mL-1) regardless of location and population. The false positive rates of the various markers in nonhuman fecal samples ranged from 5% to 47%. Results suggest that several genetic markers have considerable potential for measuring human-associated contamination in polluted environmental waters. This will be helpful in water quality monitoring, pollution modeling and health risk assessment (as demonstrated by QMRAcatch) to guide target-oriented water safety management across the globe.

Molecular detection of norovirus in sheep and pigs in New Zealand farms.

Human norovirus (NoV) is reportedly the major cause of non-bacterial gastroenteritis outbreaks worldwide and is commonly associated with water- and food-borne transmission via the faecal-oral route. Aside from humans, norovirus has been detected in pigs, cattle and mice. The close relatedness of some human and animal noroviruses has raised concerns about potential zoonotic transmission. Our laboratory recently reported the development of a multiplex real-time RT-PCR for the detection and genotyping of norovirus of genogroups I-III. Here we report a study of 56 faecal specimens from pigs and sheep that were collected and screened for noroviruses using this assay. Norovirus was found in 2/23 (9%) of porcine specimens (all were genogroup II) and in 8/33 (24%) of ovine specimens (all were genogroup III). Samples tested positive for norovirus were verified by conventional RT-PCR with different primer sets. Genomes of representative porcine and ovine norovirus strains underwent partial sequence analysis (343 and 2045 bases, respectively). This is the first report describing norovirus in sheep.

Microbial groundwater quality and its health implications for a border-strip irrigated dairy farm catchment, South Island, New Zealand.

Intensification of dairying on irrigated pastures has led to concern over the microbial quality of shallow groundwater used for drinking purposes. The effects of intensive dairying and border-strip irrigation on the leaching of E. coli and Campylobacter to shallow groundwater were assessed over a three-year period in the Waikakahi catchment, Canterbury, New Zealand. Well selection excluded other sources of contamination so that the effect of dairying with border-strip irrigation could be assessed. Groundwater samples (135) were collected, mostly during the irrigation season, with E. coli being detected in 75% of samples. Campylobacter was identified in 16 samples (12%). A risk assessment of drinking water with these levels of Campylobacter was undertaken. A probability distribution was fitted to the observed Campylobacter data and the @RISK modeling software was used, assuming a dose response relationship for Campylobacter and consumption of 1 L/day of water. The probability of infection on any given day in the study area was estimated at 0.50% to 0.76%, giving an estimated probability of infection during the irrigation season of 60% to 75%. An epidemiological assessment of the Canterbury region comparing areas encompassing dairy within major irrigation schemes (approximately 55% border-strip irrigation) to two control groups was undertaken. Control group 1 (CG1) encompasses areas of dairying without major irrigation schemes, and a second larger control group (CG2) comprises the rest of the Canterbury region. Comparisons of the subject group to control groups indicated that there was a statistically significant increase in age-standardised rates of campylobacteriosis (CG1 Relative Risk (RR)=1.51 (95% CI = 1.31-1.75); CG2 RR = 1.51 (1.33-1.72)); cryptosporidiosis (CG1 RR = 2.08 (1.55-2.79); CG2 RR = 5.33 (4.12-6.90)); and salmonellosis (CG2 RR = 2.05 (1.55-2.71)).

Evaluation of uncertainty in quantitative real-time PCR.

Quantitative real-time PCR is one of the newer methods for measurement of the amount of nucleic material in biological systems. However, reliable measurement requires an appropriate estimation of uncertainty and this paper has developed the uncertainty budget associated with this procedure using as an example, data from a quantitative real-time PCR method for the enumeration of Campylobacter jejuni. This uncertainty is relatively large and for instance, a measured result of 151 units of DNA would have a 95% confidence interval of +/-84 units of DNA with the main sources of uncertainty being the measurement of the threshold cycle (Ct) value, the predicted DNA content of the unknown sample from the calibration line and the molar absorbance value for DNA.

Rapid enumeration of Listeria monocytogenes in artificially contaminated cabbage using real-time polymerase chain reaction.

A quantitative real-time polymerase chain reaction (PCR) detection method specific for Listeria monocytogenes was developed, and studies involving pure culture showed that the response of the assay was linear over 7 log10 (log) cycles. The method was then applied to the detection of L. monocytogenes artificially inoculated onto cabbage, a vegetable chosen because it is a major component of coleslaw, which has been associated with an outbreak of listeriosis. After being allowed to attach to the food, cells were washed from the cabbage leaf surface and recovered by centrifugation. The DNA was purified by an organic solvent extraction technique and analyzed by real-time PCR. In this matrix, the method again produced a linear response over 7 log cycles from 1.4 x 10(2) to 1.4 x 10(9) CFU of L. monocytogenes in 25 g of cabbage, and analysis of the reproducibility of the system showed that log differences in L. monocytogenes numbers added to cabbage could be reliably distinguished. The system allowed quantitative results to be obtained within 8 h and was relatively inexpensive, showing good potential for routine analytical use.

Environment arrays: a possible approach for predicting changes in waterborne bacterial disease potential.

Current molecular techniques for identifying bacteria in water have proven useful, but they are not reliably predictive of impending disease outbreaks. Genomics-based approaches will help to detect the presence of pathogens quickly and well before they grow into a population that poses a risk to public health. We suggest that genomics is only one component of the toolbox that will be needed to identify emerging waterborne threats. We propose a methodology beyond genomics, based on activity in the mobile genome. This approach makes use of a new device called an environment array. The array will depend upon the same research necessary for genomics-based detection, but will not require an a priori knowledge of virulence genes. Environment arrays are assembled from molecular profiles of the infectious elements that transfer between bacteria. The advantage of the array is that it monitors the activity of the mobile genome, rather than the presence of particular DNA sequences. Environmental arrays should thus be many times more sensitive than traditional hybridization or PCR-based techniques that target already-known DNA sequences. Mobile elements are known to respond to new environmental conditions that may correlate with a chemical contamination or the bloom of bacterial pathogens, potentially allowing for a much broader application in detecting unknown or unanticipated biological and chemical contaminants.