Microbial and chemical markers: runoff transfer in animal manure-amended soils

Contribution of Manure-Spreading Operations to Bioaerosols and Antibiotic Resistance Genes' Emission

Manure spreading from farm animals can release antibiotic-resistant bacteria (ARB) carrying antimicrobial resistance genes (ARGs) into the air, posing a potential threat to human and animal health due to the intensive use of antibiotics in the livestock industry. This study analyzed the effect of different manure types and spreading methods on airborne bacterial emissions and antibiotic resistance genes in a controlled setting. Cow, poultry manure, and pig slurry were spread in a confined environment using two types of spreaders (splash plate and dribble bar), and the resulting emissions were collected before, during, and after spreading using high-volume air samplers coupled to a particle counter. Total bacteria, fecal indicators, and a total of 38 different subtypes of ARGs were further quantified by qPCR. Spreading poultry manure resulted in the highest emission rates of total bacteria (10¹¹ 16S gene copies/kg manure spread), Archaea (10⁶ 16S gene copies/kg manure), Enterococcus (10⁵ 16S gene copies/kg manure), and E. coli (10⁴ 16S gene copies/kg manure), followed by cow manure and pig slurry with splash plates and the dribble bar. Manure spreading was associated with the highest rates of airborne aminoglycoside genes for cow and poultry (10⁶ gene copies/kg manure), followed by pig slurry (10⁴ gene copies/kg manure). This study shows that the type of manure and spreading equipment can affect the emission rates of airborne bacteria, and ARGs.

Steroid-based tracing of sewage-sourced pollution of river water and wastewater treatment efficiency: Dissolved and suspended water phase distribution

In this work, the environmental distribution of steroid compounds and the level of sewage-derived contamination were assessed using sterol ratios in the confluence area of two major rivers in the Serbian capital, where raw sewage is discharged without any treatment. Special attention was paid to steroids partitioning between the dissolved and suspended phases of river and wastewater samples, since steroids tend to easily bind to particulate matter. The efficiency of sterol removal in two wastewater treatment plants in Serbia was also evaluated. Human/animal sterols coprostanol and cholesterol, and phytosterol β-sitosterol were the dominant compounds in all water samples. The sterol abundance pattern in river water was different from that in raw sewage, indicating a more pronounced biogenic input, as well as greater impact of wastewater discharges on the composition of the suspended phase. Severe contamination of the investigated area was determined, with the Danube being more contaminated than the Sava River due to different hydrodynamic conditions leading to significantly higher sterol levels in the suspended particulate matter. It was also shown that the greater part of human/animal sterols and phytosterols present in river water samples (83.0 ± 11.9 % and 87.1 ± 15.2 %) and wastewater samples (92.1 ± 6.8 % and 95.0 ± 5.7 %) was bound to suspended material compared to the dissolved phase, emphasizing the need to consider and analyze both water phases in the tracing of steroid-based environmental pollution in order to obtain a realistic picture of steroid contamination and their fate in the aquatic environment. A high removal rate (>98 %) of coprostanol and cholesterol during wastewater treatment was determined and only the coprostanol/(coprostanol + cholestanol) ratio was found to be sensitive enough to be affected by an improvement in the quality of treated wastewater.

A Bayesian inference approach to quantify average pathogen loads in farmyard manure and slurry using open-source Irish datasets

Farm-to-fork quantitative microbial risk assessments (QMRA) typically start with a preliminary estimate of initial concentration (C_initial) of microorganism loading at farm level, consisting of an initial estimate of prevalence (P) and the resulting pathogen levels in animal faeces. An average estimation of the initial concentration of pathogens can be achieved by combining P estimates in animal populations and the levels of pathogens in colonised animals' faeces and resulting cumulative levels in herd farmyard manure and slurry (FYM&S). In the present study, 14 years of data were collated and assessed using a Bayesian inference loop to assess the likely P of pathogens. In this regard, historical and current survey data exists on P estimates for a number of pathogens, including Cryptosporidium parvum, Mycobacterium avium subspecies paratuberculosis (MAP), Salmonella spp., Clostridium spp., Campylobacter spp., pathogenic E. coli, and Listeria monocytogenes in several species (cattle, pigs, and sheep) in Ireland. The results revealed that Cryptosporidium spp. has potentially the highest mean P (P_mean) (25.93%), followed by MAP (15.68%) and Campylobacter spp. (8.80%) for cattle. The P_mean of E. coli is highest (7.42%) in pigs, while the P_mean of Clostridium spp. in sheep was estimated to be 7.94%. C_initial for Cryptosporidium spp., MAP., Salmonella spp., Clostridium spp., and Campylobacter spp. in cattle faeces were derived with an average of 2.69, 4.38, 4.24, 3.46, and 3.84 log₁₀ MPN g ^-1, respectively. Average C_initial of Cryptosporidium spp., Salmonella spp., Clostridium spp., and E. coli in pig slurry was estimated as 1.27, 3.12, 3.02, and 4.48 log₁₀ MPN g ^-1, respectively. It was only possible to calculate the average C_initial of Listeria monocytogenes in sheep manure as 1.86 log₁₀ MPN g ^-1. This study creates a basis for future farm-to-fork risk assessment models to base initial pathogen loading values for animal faeces and enhance risk assessment efforts.

Fecal source tracking methods to elucidate critical sources of pathogens and contaminant microbial transport through New Zealand agricultural watersheds - A review

In New Zealand, there is substantial potential for microbial contaminants from agricultural fecal sources to be transported into waterways. The flow and transport pathways for fecal contaminants vary at a range of scales and is dependent on chemical, physical and biological attributes of pathways, soils, microorganisms and landscape characteristics. Understanding contaminant transport pathways from catchment to stream can aid water management strategies. It is not practical, however to conduct direct field measurement for all catchments on the fate and transport of fecal pathogens due to constraints on time, personnel, and material resources. To overcome this problem, fecal source tracking can be utilised to link catchment characteristics to fecal signatures identifying critical sources. In this article, we have reviewed approaches to identifying critical sources and pathways for fecal microorganisms from agricultural sources, and make recommendations for the appropriate use of these fecal source tracking (FST) tools.

Veterinary pharmaceutical contamination in mixed land use watersheds: from agricultural headwater to water monitoring watershed

Veterinary pharmaceuticals, widely used in intensive livestock production, may contaminate surface waters. Identifying their sources and pathways in watersheds is difficult because i) most veterinary pharmaceuticals are used in human medicine as well and ii) septic or sewer wastewater treatment plants (WWTP) can release pharmaceuticals into surface water, even in agricultural headwater watersheds. This study aimed to analyze the spatiotemporal variability of animal-specific, mixed-use, and human-specific pharmaceuticals, from agricultural headwaters with intensive livestock production and a WWTP to a watershed used for Water Framework Directive monitoring. Grab sampling was performed during one hydrological year upstream and downstream from a WWTP and at three dates in seven nested watersheds with areas of 1.9-84.1km². Twenty pharmaceuticals were analyzed. Animal-specific pharmaceuticals were detected at all sampling dates upstream and downstream from the WWTP and at concentrations higher than those of human-specific pharmaceuticals. The predominance of animal-specific and mixed-use pharmaceuticals vs. human-specific pharmaceuticals observed at these sampling points was confirmed at the other sampling points. Animal-specific pharmaceuticals were detected mainly during runoff events and periods of manure spreading. A large percentage of mixed-use pharmaceuticals could come from animal sources, but it was difficult to determine. Mixed-use and human-specific pharmaceuticals predominated in the largest watersheds when runoff decreased. In areas of intensive livestock production, mitigation actions should focus on agricultural headwater watersheds to decrease the number of pathways and the transfer volume of veterinary pharmaceuticals, which can be the main contaminants.

Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture

Animal waste, stream water, and streambed sediment from 19 small (<32km(2)) watersheds in 12U.S. states having either no major animal agriculture (control, n=4), or predominantly beef (n=4), dairy (n=3), swine (n=5), or poultry (n=3) were tested for: 1) cholesterol, coprostanol, estrone, and fecal indicator bacteria (FIB) concentrations, and 2) shiga-toxin producing and enterotoxigenic Escherichia coli, Salmonella, Campylobacter, and pathogenic and vancomycin-resistant enterococci by polymerase chain reaction (PCR) on enrichments, and/or direct quantitative PCR. Pathogen genes were most frequently detected in dairy wastes, followed by beef, swine and poultry wastes in that order; there was only one detection of an animal-source-specific pathogen gene (stx1) in any water or sediment sample in any control watershed. Post-rainfall pathogen gene numbers in stream water were significantly correlated with FIB, cholesterol and coprostanol concentrations, and were most highly correlated in dairy watershed samples collected from 3 different states. Although collected across multiple states and ecoregions, animal-waste gene profiles were distinctive via discriminant analysis. Stream water gene profiles could also be discriminated by the watershed animal type. Although pathogen genes were not abundant in stream water or streambed samples, PCR on enrichments indicated that many genes were from viable organisms, including several (shiga-toxin producing or enterotoxigenic E. coli, Salmonella, vancomycin-resistant enterococci) that could potentially affect either human or animal health. Pathogen gene numbers and types in stream water samples were influenced most by animal type, by local factors such as whether animals had stream access, and by the amount of local rainfall, and not by studied watershed soil or physical characteristics. Our results indicated that stream water in small agricultural U.S. watersheds was susceptible to pathogen gene inputs under typical agricultural practices and environmental conditions. Pathogen gene profiles may offer the potential to address both source of, and risks associated with, fecal pollution.

Fecal Sterol and Runoff Analysis for Nonpoint Source Tracking

Fecal pollution source identification is needed to quantify risk, target installation of source controls, and assess performance of best management practices in impaired surface waters. Sterol analysis is a chemical method for fecal source tracking that allows for differentiation between several fecal pollution sources. The objectives of this study were to use these chemical tracers for quantifying human fecal inputs in a mixed-land-use watershed without point sources of pollution and to determine the relationship between land use and sterol ratios. Fecal sterol analysis was performed on bed and suspended sediment from impaired streams. Human fecal signatures were found at sites with sewer overflow and septic inputs. Different sterol ratios used to indicate human fecal pollution varied in their sensitivity. Next, geospatial data was used to determine the runoff volumes associated with each land-use category in the watersheds. Fecal sterol ratios were compared between sampling locations and correlations were tested between ratio values and percentage of runoff for a given land-use category. Correlation was not observed between percentage of runoff from developed land and any of the five tested human-indicating sterol ratios in streambed sediments, confirming that human fecal inputs were not evenly distributed across the urban landscape. Several practical considerations for adopting this chemical method for microbial source tracking in small watersheds are discussed. Results indicate that sterol analysis is useful for identifying the location of human fecal nonpoint-source inputs.

A short review of fecal indicator bacteria in tropical aquatic ecosystems: knowledge gaps and future directions

Given the high numbers of deaths and the debilitating nature of diseases caused by the use of unclean water it is imperative that we have an understanding of the factors that control the dispersion of water borne pathogens and their respective indicators. This is all the more important in developing countries where significant proportions of the population often have little or no access to clean drinking water supplies. Moreover, and notwithstanding the importance of these bacteria in terms of public health, at present little work exists on the persistence, transfer and proliferation of these pathogens and their respective indicator organisms, e.g., fecal indicator bacteria (FIB) such as Escherichia coli and fecal coliforms in humid tropical systems, such as are found in South East Asia or in the tropical regions of Africa. Both FIB and the waterborne pathogens they are supposed to indicate are particularly susceptible to shifts in water flow and quality and the predicted increases in rainfall and floods due to climate change will only exacerbate the problems of contamination. This will be furthermore compounded by the increasing urbanization and agricultural intensification that developing regions are experiencing. Therefore, recognizing and understanding the link between human activities, natural process and microbial functioning and their ultimate impacts on human health are prerequisites for reducing the risks to the exposed populations. Most of the existing work in tropical systems has been based on the application of temperate indicator organisms, models and mechanisms regardless of their applicability or appropriateness for tropical environments. Here, we present a short review on the factors that control FIB dynamics in temperate systems and discuss their applicability to tropical environments. We then highlight some of the knowledge gaps in order to stimulate future research in this field in the tropics.

Detection of pathogens, indicators, and antibiotic resistance genes after land application of poultry litter

Poultry litter (PL) is a by-product of broiler production. Most PL is land applied. Land-applied PL is a valuable nutrient source for crop production but can also be a route of environmental contamination with manure-borne bacteria. The objective of this study was to characterize the fate of pathogens, fecal indicator bacteria (FIB), and bacteria containing antibiotic resistance genes (ARGs) after application of PL to soils under conventional till or no-till management. This 2-yr study was conducted in accordance with normal agricultural practices, and microbial populations were quantified using a combination of culture and quantitative, real-time polymerase chain reaction analysis. Initial concentrations of in PL were 5.4 ± 3.2 × 10 cells g PL; sp. was not detected in the PL but was enriched periodically from PL-amended soils. was detected in PL (1.5 ± 1.3 × 10 culturable or 1.5 ± 0.3 × 10 genes g) but was rarely detected in field soils, whereas enterococci (1.5 ± 0.5 × 10 cells g PL) were detected throughout the study. These results suggest that enterococci may be better FIB for field-applied PL. Concentrations of ARGs for sulfonamide, streptomycin, and tetracycline resistance increased up to 3.0 orders of magnitude after PL application and remained above background for up to 148 d. These data provide new knowledge about important microbial FIB, pathogens, and ARGs associated with PL application under realistic field-based conditions.

Microbial contamination detection in water resources: interest of current optical methods, trends and needs in the context of climate change

Microbial pollution in aquatic environments is one of the crucial issues with regard to the sanitary state of water bodies used for drinking water supply, recreational activities and harvesting seafood due to a potential contamination by pathogenic bacteria, protozoa or viruses. To address this risk, microbial contamination monitoring is usually assessed by turbidity measurements performed at drinking water plants. Some recent studies have shown significant correlations of microbial contamination with the risk of endemic gastroenteresis. However the relevance of turbidimetry may be limited since the presence of colloids in water creates interferences with the nephelometric response. Thus there is a need for a more relevant, simple and fast indicator for microbial contamination detection in water, especially in the perspective of climate change with the increase of heavy rainfall events. This review focuses on the one hand on sources, fate and behavior of microorganisms in water and factors influencing pathogens' presence, transportation and mobilization, and on the second hand, on the existing optical methods used for monitoring microbiological risks. Finally, this paper proposes new ways of research.

Soil Nutrients, Bacteria Populations, and Veterinary Pharmaceuticals across a Backgrounding Beef Feedlot

Beef cattle backgrounding operations that grow out weaned calves for feedlot finishing contain several environmentally significant constituents. A better understanding of these constituents and their environmental distribution will aid in the development of effective management guidelines for sustainable beef production. This research investigated soil nutrients, bacterial, and veterinary pharmaceutical concentrations across a small backgrounding beef feedlot on a karst landscape. Results indicated that all contaminants were highly concentrated in the feeder area (FD) and were lower in the other feedlot areas. The FD soils had a pH of 8.2, 59 mg kg soil organic matter (SOM), 2002 mg kg soil test phosphorus (STP), 99.7 mg kg NH-N, and 18.3 mg kg NO-N. The other locations were acidic (5.9-6.9 pH) and contained 39 mg kg SOM, 273 mg kg STP, 21.5 mg kg NH-N, and 2.0 NO-N mg kg. Bacteria populations in the FD averaged 2.7 × 10 total cells, 3.9 × 10 spp., 2.9 × 10 spp, and 4.5 × 10 cells per gram of soil. spp. and spp. concentrations were 1 to 4 orders of magnitude lower at the other locations. showed lower dynamic range and was generally uniformly distributed across the landscape. Antibiotic and parasiticide concentrations in the FD were 86.9 ng g monensin, 25.0 ng g lasalocid, and 10.3 ng g doramectin. Their concentrations were 6- to 27-fold lower in the other feedlot locations. Contaminant management plans for this small feedlot will therefore focus on the feeder and nearby grazing areas where soil nutrients, bacteria populations, and veterinary pharmaceuticals were most concentrated.

Origin of fecal contamination in waters from contrasted areas: stanols as Microbial Source Tracking markers

Improving the microbiological quality of coastal and river waters relies on the development of reliable markers that are capable of determining sources of fecal pollution. Recently, a principal component analysis (PCA) method based on six stanol compounds (i.e. 5β-cholestan-3β-ol (coprostanol), 5β-cholestan-3α-ol (epicoprostanol), 24-methyl-5α-cholestan-3β-ol (campestanol), 24-ethyl-5α-cholestan-3β-ol (sitostanol), 24-ethyl-5β-cholestan-3β-ol (24-ethylcoprostanol) and 24-ethyl-5β-cholestan-3α-ol (24-ethylepicoprostanol)) was shown to be suitable for distinguishing between porcine and bovine feces. In this study, we tested if this PCA method, using the above six stanols, could be used as a tool in "Microbial Source Tracking (MST)" methods in water from areas of intensive agriculture where diffuse fecal contamination is often marked by the co-existence of human and animal sources. In particular, well-defined and stable clusters were found in PCA score plots clustering samples of "pure" human, bovine and porcine feces along with runoff and diluted waters in which the source of contamination is known. A good consistency was also observed between the source assignments made by the 6-stanol-based PCA method and the microbial markers for river waters contaminated by fecal matter of unknown origin. More generally, the tests conducted in this study argue for the addition of the PCA method based on six stanols in the MST toolbox to help identify fecal contamination sources. The data presented in this study show that this addition would improve the determination of fecal contamination sources when the contamination levels are low to moderate.

Real-time estimation of small-area populations with human biomarkers in sewage

A new approach is conceptualized for measuring small-area human populations by using biomarkers in sewage. The basis for the concept (SCIM: Sewage Chemical-Information Mining) is supported by a comprehensive examination and synthesis of data published across several disciplines, including medicine, microbiology, clinical chemistry, and environmental science. Accurate measures of human populations are fundamental to numerous disciplines, including economics, marketing, politics, sociology, public health and safety (e.g., disease management; assessment of natural hazards; disaster prevention and response), quality of life, and the environment. Knowing the size, distribution, and flow of a small-area (local) population facilitates understanding the numerous and complex linkages and interactions between humans and the environment. Examples include material-flow (substance-flow) analysis, determining the magnitude of per capita contribution of pollutant loadings to watersheds, or forecasting future impacts of local populations on the environment or a population's demands on resources. While no definitive approach exists for measuring small-area populations, census-taking is a long-established convention. No approach exists, however, for gauging small-area populations in real-time, as none is able to capture population dynamics, which involve transient changes (e.g., daily influx and efflux) and lasting changes (e.g., births, deaths, change in residence). Accurate measurement of small-area populations in real time has never been possible but is essential for facilitating the design of more sustainable communities. Real-time measurement would provide communities the capability of testing what-if scenarios in design and policy decisions. After evaluation of a range of biomarkers (including the nitrogenous waste product creatinine, which has been long used in clinical chemistry as a parameter to normalize the concentrations of other urinary excretion products to account for urine dilution), the biomarker with the most potential for the SCIM concept for real-time measurement of population was determined to be coprostanol - the major sterol produced by microbial reduction of cholesterol in the colon.