Survival, mobilization, and transport of Escherichia coli from sheep faeces.

AIMS: This study looked at the survival, mobilization, and transport of Escherichia coli from sheep faeces over an extended period, which was then repeated for all four seasons. METHODS AND RESULTS: Rain simulation was used to measure E. coli mobilization directly from faecal pats and subsequent transport across a soil surface. The rain simulation experiments were conducted over the same 90-day period and for the four seasons as per the survival experiments conducted to determine E. coli survival in faecal pats. The survival experiments demonstrated up to three orders of magnitude increase of E. coli in sheep faeces. Peak E. coli concentrations in the faeces were observed on Day 2 through to Day 30, with no significant effect of seasons or weather patterns. The E. coli concentrations in the runoff followed the survival pattern of E. coli concentrations in the faeces. CONCLUSIONS: There was a statistically significant relationship between the E. coli concentrations in the faeces and the runoff. SIGNIFICANCE AND IMPACT OF STUDY: The data generated on the relationship between Escherichia coli concentrations in the faeces and in the runoff can support the development of runoff risk models for sheep grazing pastureland to support catchment modelling, land use decisions, and public health.

A Heuristic Method for Determining Changes of Source Loads to Comply with Water Quality Limits in Catchments.

A common land and water management task is to determine where and by how much source loadings need to change to meet water quality limits in receiving environments. This paper addresses the problem of quantifying changes in loading when limits are specified in many locations in a large and spatially heterogeneous catchment, accounting for cumulative downstream impacts. Current approaches to this problem tend to use either scenario analysis or optimization, which suffer from difficulties of generating scenarios that meet the limits, or high complexity of optimization approaches. In contrast, we present a novel method in which simple catchment models, load limits, upstream/downstream spatial relationships and spatial allocation rules are combined to arrive at source load changes. The process iteratively establishes the critical location (river segment or lake) where the limits are most constraining, and then adjusts sources upstream of the critical location to meet the limit at that location. The method is demonstrated with application to New Zealand (268,000 km2) for nutrients and the microbial indicator E. coli, which was conducted to support policy development regarding water quality limits. The model provided useful insights, such as a source load excess (the need for source load reduction) even after mitigation measures are introduced in order to comply with E. coli limits. On the other hand, there was headroom (ability to increase source loading) for nutrients. The method enables assessment of the necessary source load reductions to achieve water quality limits over broad areas such as large catchments or whole regions.

Variability of Escherichia coli Concentrations in Rivers during Base-Flow Conditions in New Zealand.

concentrations in rivers are known to vary considerably. Much research has focused on storm events and the relationships between fecal microbe concentrations and flows. However, there is still considerable variability in microbial concentrations during base-flow conditions, and little research has been conducted to understand this short-term variability in rivers. We investigated the variability of concentrations in base flows at the time scales of minutes, hours, and days and compared this to variability from laboratory replication of the measurement methods. This was conducted in three different-sized rivers in both summer and winter seasons. Estimates of variability were analyzed using the coefficient of variation (CV). The variability at the minute time scale was 17%, compared with the laboratory replication variability of 15%. The CV then increased to approximately 32 and 60% at the hourly and daily time scales, respectively. There is strong evidence that both time scale ( < 0.001) and river ( < 0.001) significantly affect the variation in concentrations. The concentrations were higher in summer than winter, with a marked effect in the smallest stream, where at one site the concentrations were >2000 most probable number (mpn) 100 mL in all summer samples. This variability of concentrations should be considered when interpreting the results from a one-off grab sample used to compare against water quality standards or for calibrating models.

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream.

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation.

Mapping of Escherichia coli Sources Connected to Waterways in the Ruamahanga Catchment, New Zealand.

Rivers and streams in New Zealand are natural with free access and used by many people for swimming and fishing. However, pastoral farming with free grazing animals is a common land use in New Zealand and faecal microorganisms from them often end up in waterways. These microorganisms can seriously affect human and animal health if ingested. This paper describes spatial modeling using GIS of Escherichia coli sources in a large catchment (350 000 ha), the Ruamahanga. By examining the pathway of water over and through soils, it is possible to determine whether E. coli sources are connected to waterways or not. The map of E. coli sources connected to waterways provides useful context to those setting water quality limits. This approach avoids the complexity of modeling the fate and transport of E. coli in waterways, yet still permits the assessment of catchment-wide mitigation and best management practice. Fencing of waterways would minimize E. coli sources directly defecated to water and would reduce total E. coli sources by approximately 35%. Introduction of dung beetles would minimize sources connected to waterways by overland flow and would reduce total E. coli sources by approximately 35%. Construction of dairy effluent ponds would minimize sources connected to waterways through high bypass flow in soils and would reduce total E. coli sources by approximately 25%.

A farm-scale risk-index for reducing fecal contamination of surface waters.

There is increasing recognition of the adverse impacts of agricultural practices on microbial water quality leading to increased expectation on farmers to manage environmental impacts on water quality. Therefore, farmers require a tool to help them prioritize mitigations targeted at reducing fecal contamination of surface water. A farm-scale risk-index was developed from modeled data on the predicted losses of from selected farm practices. The farm-scale data were then converted to a catchment scale risk value and calibrated against stream concentration data measured in five catchments. The data from the five catchments indicate that there is a relationship between the risk of losses from some farm practices and the resulting levels in the streams. The results show that the adoption of existing mitigation options for fecal contamination should result in a substantial reduction of concentrations in streams flowing through catchments used for intensive dairy farming. However, the relatively high concentrations in the stream when the calculated risk-index values are low indicate that currently available mitigation practices may not be sufficient to achieve contact recreational water quality standards in many catchments due to other sources of . This risk-index approach can be incorporated into existing decision support tools to enable farmers to manage fecal contamination impacts from their farming operations.

High-resolution genomic analysis to investigate the impact of the invasive brushtail possum (Trichosurus vulpecula) and other wildlife on microbial water quality assessments.

Escherichia coli are routine indicators of fecal contamination in water quality assessments. Contrary to livestock and human activities, brushtail possums (Trichosurus vulpecula), common invasive marsupials in Aotearoa/New Zealand, have not been thoroughly studied as a source of fecal contamination in freshwater. To investigate their potential role, Escherichia spp. isolates (n = 420) were recovered from possum gut contents and feces and were compared to those from water, soil, sediment, and periphyton samples, and from birds and other introduced mammals collected within the Makirikiri Reserve, Dannevirke. Isolates were characterized using E. coli-specific real-time PCR targeting the uidA gene, Sanger sequencing of a partial gnd PCR product to generate a gnd sequence type (gST), and for 101 isolates, whole genome sequencing. Escherichia populations from 106 animal and environmental sample enrichments were analyzed using gnd metabarcoding. The alpha diversity of Escherichia gSTs was significantly lower in possums and animals compared with aquatic environmental samples, and some gSTs were shared between sample types, e.g., gST535 (in 85% of samples) and gST258 (71%). Forty percent of isolates gnd-typed and 75% of reads obtained by metabarcoding had gSTs shared between possums, other animals, and the environment. Core-genome single nucleotide polymorphism (SNP) analysis showed limited variation between several animal and environmental isolates (<10 SNPs). Our data show at an unprecedented scale that Escherichia clones are shared between possums, other wildlife, water, and the wider environment. These findings support the potential role of possums as contributors to fecal contamination in Aotearoa/New Zealand freshwater. Our study deepens the current knowledge of Escherichia populations in under-sampled wildlife. It presents a successful application of high-resolution genomic methods for fecal source tracking, thereby broadening the analytical toolbox available to water quality managers. Phylogenetic analysis of isolates and profiling of Escherichia populations provided useful information on the source(s) of fecal contamination and suggest that comprehensive invasive species management strategies may assist in restoring not only ecosystem health but also water health where microbial water quality is compromised.

Development of a multiplex droplet digital PCR assay for simultaneous detection and quantification of Escherichia coli, E. marmotae, and E. ruysiae in water samples.

Escherichia coli are widely used by water quality managers as Fecal Indicator Bacteria, but current quantification methods do not differentiate them from benign, environmental Escherichia species such as E. marmotae (formerly named cryptic clade V) or E. ruysiae (cryptic clades III and IV). Reliable and specific techniques for their identification are required to avoid confounding microbial water quality assessments. To address this, a multiplex droplet digital PCR (ddPCR) assay targeting lipB (E. coli and E. ruysiae) and bglC (E. marmotae) was designed. The ddPCR performance was assessed using in silico analysis; genomic DNA from 40 local, international, and reference strains of target and non-target coliforms; and spiked water samples in a range relevant to water quality managers (1 to 1000 cells/100 mL). Results were compared to an analogous quantitative PCR (qPCR) and the Colilert method. Both PCR assays showed excellent sensitivity with a limit of detection of 0.05 pg/µL and 0.005 pg/µl for ddPCR and qPCR respectively, and of quantification of 0.5 pg/µL of genomic DNA. The ddPCR allowed differentiation and quantification of three Escherichia species per run by amplitude multiplexing and showed a high concordance with concentrations measured by Colilert once proportional bias was accounted for. In silico specificity testing underlined the possibility to further detect and distinguish Escherichia cryptic clade VI. Finally, the applicability of the ddPCR was successfully tested on environmental water samples where E. marmotae and E. ruysiae potentially confound E. coli counts based on the Most Probable Number method, highlighting the utility of this novel ddPCR as an efficient and rapid discriminatory test to improve water quality assessments.

Draft genome sequences of Escherichia spp. isolates from New Zealand environmental sources.

Escherichia coli is often used as a fecal indicator bacterium for water quality monitoring. We report the draft genome sequences of 500 Escherichia isolates including newly described Escherichia species, namely Escherichia marmotae, Escherichia ruysiae, and Escherichia whittamii, obtained from diverse environmental sources to assist with improved public health risk assessments.

Escherichia coli runoff from sheep and dairy cow grazed pasture: A plot scale simulation.

Animal agriculture is recognized as a key source of fecal microbial impacts on water quality and associated risks to human health. Most of the research effort has focused on losses of fecal microbes from cow/cattle feces with little research effort on sheep fecal risks. The literature on fecal microbial risks from pasture is complicated by the fact that experiments are carried out in different environments leading to difficulties in making direct comparisons between sheep and cow/cattle losses from pasture areas. In this study, a plot scale simulation was conducted on the same pasture plots, using simulated rainfall to generate comparable runoff conditions, and using simulated grazing to create similar relative stocking rates. The Escherichia coli concentrations in the runoff were similar from simulated or natural rainfall events. At an equivalent stocking rate, the E. coli runoff concentrations from the sheep grazed pastures were four times higher than the cow grazed pasture. These results show that at an equivalent stocking rate, the E. coli runoff risk from sheep grazed pasture is higher than for cow grazed pasture. Further research is needed to understand the relative impacts of different grazing species of animals as well as stocking rate or management effects on these relative risks to water quality.

Differences in the fecal concentrations and genetic diversities of Campylobacter jejuni populations among individual cows in two dairy herds.

Dairy cows have been identified as common carriers of Campylobacter jejuni, which causes many of the human gastroenteritis cases reported worldwide. To design on-farm management practices that control the human infection sourced from dairy cows, the first step is to acquire an understanding of the excretion patterns of the cow reservoir. We monitored the same 35 cows from two dairy farms for C. jejuni excretion fortnightly for up to 12 months. The objective was to examine the concentration of C. jejuni and assess the genetic relationship of the C. jejuni populations excreted by individual cows. Significant differences (P < 0.01) in C. jejuni fecal concentration were observed among the 35 cows, with median concentrations that varied by up to 3.6 log(10) · g(-1) feces. A total of 36 different genotypes were identified from the 514 positive samples by using enterobacterial repetitive intergenic consensus (ERIC)-PCR. Although 22 of these genotypes were excreted by more than one cow, the analysis of frequencies and distribution of the genotypes by model-based statistics revealed a high degree of individuality in the C. jejuni population in each cow. The observed variation in the frequency of excretion of a genotype among cows and the analysis by multilocus sequence typing (MLST) of these genotypes suggest that excretion of C. jejuni in high numbers is due to a successful adaptation of a particular genotype to a particular cow's gut environment, but that animal-related factors render some individual cows resistant to colonization by particular genotypes. The reasons for differences in C. jejuni colonization of animals warrant further investigation.

Differential behaviour of Escherichia coli and Campylobacter spp. in a stream draining dairy pasture.

The faecal indicator bacterium Escherichia coli and thermotolerant Campylobacter spp., which are potentially pathogenic, were investigated in the Toenepi Stream draining a pastoral catchment dominated by dairying. Bacteria concentrations were monitored routinely at fortnightly intervals over 12 months and intensively during storm events to compare the transport dynamics of bacterial indicator and pathogen under varying hydro-meteorological conditions. Routine monitoring indicated median concentrations of 345 E. coli MPN 100 ml(-1) and relatively low concentrations of 2.3 Campylobacter MPN 100 ml(-1). The bacterial flux was three orders of magnitude greater under elevated stream flow compared with base-flow. E. coli peak concentrations occurred very close to the turbidity peak and consistently ahead of the Campylobacter spp. peak (which was close to the hydrograph peak). We postulate that, under flood conditions, the E. coli peak reflects the entrainment and mobilisation of in-stream stores on the flood wave front. In contrast, Campylobacter spp. are derived from wash-in from land stores upstream and have travelled at the mean water velocity which is slower than the speed of the flood wave. Our findings of different dynamics for E. coli and Campylobacter spp. suggest that mitigation to reduce faecal microbial impacts from farms will need to take account of these differences.

Lyophilization prior to direct DNA extraction from bovine feces improves the quantification of Escherichia coli O157:H7 and Campylobacter jejuni.

Lyophilization was used to concentrate bovine feces prior to DNA extraction and analysis using real-time PCR. Lyophilization significantly improved the sensitivity of detection compared to that in fresh feces and was associated with reliable quantification of both Escherichia coli O157:H7 and Campylobacter jejuni bacteria present in feces at concentrations ranging between 2 log(10) and 6 log(10) CFU g(-)(1).

Applications of the Soil, Plant and Rumen Microbiomes in Pastoral Agriculture.

The production of dairy, meat, and fiber by ruminant animals relies on the biological processes occurring in soils, forage plants, and the animals' rumens. Each of these components has an associated microbiome, and these have traditionally been viewed as distinct ecosystems. However, these microbiomes operate under similar ecological principles and are connected via water, energy flows, and the carbon and nitrogen nutrient cycles. Here, we summarize the microbiome research that has been done in each of these three environments (soils, forage plants, animals' rumen) and investigate what additional benefits may be possible through understanding the interactions between the various microbiomes. The challenge for future research is to enhance microbiome function by appropriate matching of plant and animal genotypes with the environment to improve the output and environmental sustainability of pastoral agriculture.

Development and evaluation of the bacterial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model.

The Agricultural Policy/Environmental eXtender (APEX) is a watershed-scale water quality model that includes detailed representation of agricultural management. The objective of this work was to develop a process-based model for simulating the fate and transport of manure-borne bacteria on land and in streams with the APEX model. The bacteria model utilizes manure erosion rates to estimate the amount of edge-of-field bacteria export. Bacteria survival in manure is simulated as a two-stage process separately for each manure application event. In-stream microbial fate and transport processes include bacteria release from streambeds due to sediment resuspension during high flow events, active release from the streambed sediment during low flow periods, bacteria settling with sediment, and survival. Default parameter values were selected from published databases and evaluated based on field observations. The APEX model with the newly developed microbial fate and transport module was applied to simulate fate and transport of the fecal indicator bacterium Escherichia coli in the Toenepi watershed, New Zealand that was monitored for seven years. The stream network of the watershed ran through grazing lands with daily bovine waste deposition. Results show that the APEX with the bacteria module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water as affected by various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.

Transcriptome Changes of Escherichia coli, Enterococcus faecalis, and Escherichia coli O157:H7 Laboratory Strains in Response to Photo-Degraded DOM.

In this study, we investigated gene expression changes in three bacterial strains (Escherichia coli C3000, Escherichia coli O157:H7 B6914, and Enterococcus faecalis ATCC 29212), commonly used as indicators of water quality and as control strains in clinical, food, and water microbiology laboratories. Bacterial transcriptome responses from pure cultures were monitored in microcosms containing water amended with manure-derived dissolved organic matter (DOM), previously exposed to simulated sunlight for 12 h. We used RNA sequencing (RNA-seq) and quantitative real-time reverse transcriptase (qRT-PCR) to compare differentially expressed temporal transcripts between bacteria incubated in microcosms containing sunlight irradiated and non-irradiated DOM, for up to 24 h. In addition, we used whole genome sequencing simultaneously with RNA-seq to identify single nucleotide variants (SNV) acquired in bacterial populations during incubation. These results indicate that E. coli and E. faecalis have different mechanisms for removal of reactive oxygen species (ROS) produced from irradiated DOM. They are also able to produce micromolar concentrations of H2O2 from non-irradiated DOM, that should be detrimental to other bacteria present in the environment. Notably, this study provides an assessment of the role of two conjugative plasmids carried by the E. faecalis and highlights the differences in the overall survival dynamics of environmentally-relevant bacteria in the presence of naturally-produced ROS.

Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities.

Natural waters serve as habitat for a wide range of microorganisms, a proportion of which may be derived from fecal material. A number of watershed models have been developed to understand and predict the fate and transport of fecal microorganisms within complex watersheds, as well as to determine whether microbial water quality standards can be satisfied under site-specific meteorological and/or management conditions. The aim of this review is to highlight and critically evaluate developments in the modeling of microbial water quality of surface waters over the last 10 years and to discuss the future of model development and application at the watershed scale, with a particular focus on fecal indicator organisms (FIOs). In doing so, an agenda of research opportunities is identified to help deliver improvements in the modeling of microbial water quality draining through complex landscape systems. This comprehensive review therefore provides a timely steer to help strengthen future modeling capability of FIOs in surface water environments and provides a useful resource to complement the development of risk management strategies to reduce microbial impairment of freshwater sources.

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments.

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.

A model framework to assess the effect of dairy farms and wild fowl on microbial water quality during base-flow conditions.

There is concern regarding microbial water quality in many pastoral catchments in New Zealand which are home to numerous livestock and wild animals. Information on microbial impacts on water quality from these animals is scarce. A framework is needed to summarise our current knowledge and identify gaps at the scale of an individual farm. We applied a Monte Carlo modelling approach to a hypothetical dairy farm based on the extensive data sets available for the Toenepi Catchment, Waikato, New Zealand. The model focused on quantifiable direct inputs to the stream from ducks, cows and farm dairy effluent (FDE) during base-flow conditions. Most of the inputs of Escherichia coli from dairy farms occur sporadically and, therefore, have little effect on the expected median stream concentrations. These sporadic inputs do however, have a strong influence on extrema such as 95th percentile values. Current farm mitigations of fencing streams and using improved management practices for applying FDE to land, such as low application rate deferred FDE irrigation systems, would appreciably reduce faecal microbial inputs to the stream. However, the concentrations of E. coli in rural streams may not reduce as much as expected as wild fowl living in streams would have a larger effect on water quality than a farm in which environmental mitigations are widely implemented.

Interaction of Escherichia coli and soil particles in runoff.

A laboratory-scale model system was developed to investigate the transport mechanisms involved in the horizontal movement of bacteria in overland flow across saturated soils. A suspension of Escherichia coli and bromide tracer was added to the model system, and the bromide concentration and number of attached and unattached E. coli cells in the overland flow were measured over time. Analysis of the breakthrough curves indicated that the E. coli and bromide were transported together, presumably by the same mechanism. This implied that the E. coli was transported by advection with the flowing water. Overland-flow transport of E. coli could be significantly reduced if the cells were preattached to large soil particles (> 45 microm). However, when unattached cells were inoculated into the system, the E. coli appeared to attach predominantly to small particles (< 2 microm) and hence remained unattenuated during transport. These results imply that in runoff generated by saturation-excess conditions, bacteria are rapidly transported across the surface and have little opportunity to interact with the soil matrix.