Microbial life in preferential flow paths in subsurface clayey till revealed by metataxonomy and metagenomics.

BACKGROUND: Subsurface microorganisms contribute to important ecosystem services, yet little is known about how the composition of these communities is affected by small scale heterogeneity such as in preferential flow paths including biopores and fractures. This study aimed to provide a more complete characterization of microbial communities from preferential flow paths and matrix sediments of a clayey till to a depth of 400 cm by using 16S rRNA gene and fungal ITS2 amplicon sequencing of environmental DNA. Moreover, shotgun metagenomics was applied to samples from fractures located 150 cm below ground surface (bgs) to investigate the bacterial genomic adaptations resulting from fluctuating exposure to nutrients, oxygen and water. RESULTS: The microbial communities changed significantly with depth. In addition, the bacterial/archaeal communities in preferential flow paths were significantly different from those in the adjacent matrix sediments, which was not the case for fungal communities. Preferential flow paths contained higher abundances of 16S rRNA and ITS gene copies than the corresponding matrix sediments and more aerobic bacterial taxa than adjacent matrix sediments at 75 and 150 cm bgs. These findings were linked to higher organic carbon and the connectivity of the flow paths to the topsoil as demonstrated by previous dye tracer experiments. Moreover, bacteria, which were differentially more abundant in the fractures than in the matrix sediment at 150 cm bgs, had higher abundances of carbohydrate active enzymes, and a greater potential for mixotrophic growth. CONCLUSIONS: Our results demonstrate that the preferential flow paths in the subsurface are unique niches that are closely connected to water flow and the fluctuating ground water table. Although no difference in fungal communities were observed between these two niches, hydraulically active flow paths contained a significantly higher abundance in fungal, archaeal and bacterial taxa. Metagenomic analysis suggests that bacteria in tectonic fractures have the genetic potential to respond to fluctuating oxygen levels and can degrade organic carbon, which should result in their increased participation in subsurface carbon cycling. This increased microbial abundance and activity needs to be considered in future research and modelling efforts of the soil subsurface.

N-Map: High-resolution groundwater N-retention mapping and modelling by integration of geophysical, geological, geochemical, and hydrological data.

A key aspect of protecting aquatic ecosystems from agricultural nitrogen (N) is to locate (i) farmlands where nitrate leaches from the bottom of the root zone and (ii) denitrifying zones in the aquifers where nitrate is removed before entering the surface water (N-retention). N-retention affects the choice of field mitigation measures to reduce delivered N to surface water. Farmland parcels associated with high N-retention gives the lowest impact of the targeted field measures and vice versa. In Denmark, a targeted N-regulation approach is currently implemented on small catchment scale (approx. 15 km2). Although this regulatory scale is much more detailed than what has been used previously, it is still so large that regulation for most individual fields will be either over- or under-regulated due to large spatial variation in the N-retention. The potential cost reduction for farmers is of up to 20-30% from detailed retention mapping at the field scale compared to the current small catchment scale. In this study, we present a mapping framework (N-Map) for differentiating farmland according to their N-retention, which can be used for improving the effectiveness of targeted N-regulation. The framework currently only includes N-retention in the groundwater. The framework benefits from the incorporation of innovative geophysics in hydrogeological and geochemical mapping and modelling. To capture and describe relevant uncertainties a large number of equally probable realizations are created through Multiple Point Statistical (MPS) methods. This allows relevant descriptions of uncertainties of parts of the model structure and includes other relevant uncertainty measures that affects the obtained N-retention. The output is data-driven high-resolution groundwater N-retention maps, to be used by the individual farmers to manage their cropping systems due to the given regulatory boundary conditions. The detailed mapping allows farmers to use this information in the farm planning in order to optimize the use of field measures to reduce delivered agricultural N to the surface water and thereby lower the costs of the field measures. From farmer interviews, however, it is clear that not all farms will have an economic gain from the detailed mapping as the mapping costs will exceed the potential economic gains for the farmers. The costs of N-Map is here estimated to 5-7 €/ha/year plus implementation costs at the farm. At the society level, the N-retention maps allow authorities to point out opportunities for a more targeted implementation of field measures to efficiently reduce the delivered N-load to surface waters.

Upscaling of Denitrification Rates from Point to Catchment Scales for Modeling of Nitrate Transport and Retention.

The spatial and temporal variability of denitrification makes it challenging to integrate conceptual, process-based understandings of nitrate transport and retention into numerical modeling at the catchment scale, although it is critical for the realism and predictive power of the model. In this study, we propose a novel approach where the conceptual understandings of the spatial structure of denitrification zones and the corresponding representative denitrification rates are transformed into a form that can be integrated into a multi-point statistical simulation framework. This is done by constructing a denitrification training image (TI) coupled to a geophysically based TI of the hydrogeological structure. The field observations and laboratory analyses of denitrification rates and the chemistry of water and sediment revealed that the study catchment's subsurface can be characterized by three zones: (1) the oxic zone with no nitrate reduction; (2) the slow-denitrification zone (mean of ln-transformed rate = -1.19 ± 0.52 mg N L-1 yr-1); and (3) the high-denitrification zone (mean of ln-transformed rate = 3.86 ± 1.96 mg N L-1 yr-1). The underlying controls on the spatial distribution of these zones and the representativeness of denitrification rates were investigated. Then, a TI illustrating the subsurface structure of the denitrification zone was constructed by synthesizing the results of these geochemical interpretations and the hydrogeology TI.

History and Sources of Co-Occurring Pesticides in an Abstraction Well Unraveled by Age Distributions of Depth-Specific Groundwater Samples.

When groundwater-based drinking water supply becomes contaminated, the timing and source of contamination are obvious questions. However, contaminants often have diffuse sources and different contaminants may have different sources even in a single groundwater well, making these questions complicated to answer. Age dating of groundwater has been used to reconstruct contaminant travel times to wells; however, critics have highlighted that groundwater flow is often complex with mixing of groundwater of different ages. In drinking water wells, where water is typically abstracted from a large depth interval, such mixing is even more problematic. We present a way to overcome some of the obstacles in identifying the source and age of contaminants in drinking water wells by combining depth-specific sampling with age tracer modeling, particle tracking simulations, geological characterization, and contaminant properties. This multitool approach was applied to a drinking water well, where bentazon and dichlorprop contamination was found to have different pollutant sources and release histories, even though both pesticides can be associated with the same land use. Bentazon was derived from recent application to a golf course, while dichlorprop was derived from agricultural use more than 30 years ago. The advantages, limitations, and pitfalls of the proposed course of action are then further discussed.

Adhesion to sand and ability to mineralise low pesticide concentrations are required for efficient bioaugmentation of flow-through sand filters.

Pesticide-polluted drinking water may be remediated by inoculating waterworks sand filters with specific degrading bacteria. However, degradation efficiency is often hampered by the poor adhesion behaviour of the introduced bacteria. The phenoxy acid herbicide 4-chloro-2-methyl-phenoxy-acetic acid (MCPA) is a widespread groundwater contaminant. The aim of this study was to investigate whether specific surface characteristics of MCPA-degrading bacteria could be linked to their degrading capabilities in sand filters. Four MCPA degraders with different taxonomic affiliations and original habitats (Sphingomonas sp. PM2, Sphingomonas sp. ERG5, Burkholderia sp. TFD34, Cupriavidus sp. TFD38) were characterised with regard to their motility, cell surface hydrophobicity, biofilm formation, adhesion behaviour and ability to mineralise MCPA. Strains PM2 and ERG5 were non-motile and hydrophobic, whilst strains TFD34 and TFD38 were motile and less hydrophobic. All the strains except ERG5 showed low biofilm formation on polystyrene, although it was significantly higher on glass. PM2 was the most efficient MCPA degrader as it displayed no lag phase and reached >50 % mineralisation at all concentrations (0.0016-25 mg L-1). PM2 adhered significantly better to sand than the other strains. No link was found between motility, biofilm formation and the ability to adhere to sand. PM2 completely removed MCPA for 14 days when inoculated in sand columns with a constant inlet of 1 mg L-1 MCPA. These results demonstrate that besides the ability to degrade the contaminant, surface hydrophobicity and adherence abilities are significant parameters controlling sustained degradation in flow-through sand columns and must be considered when selecting bacteria for bioaugmentation.

Groundwater contamination with 2,6-dichlorobenzamide (BAM) and perspectives for its microbial removal.

The pesticide metabolite 2,6-dichlorobenzamide (BAM) is very persistent in both soil and groundwater and has become one of the most frequently detected groundwater micropollutants. BAM is not removed by the physico-chemical treatment techniques currently used in drinking water treatment plants (DWTP); therefore, if concentrations exceed the legal threshold limit, it represents a sizeable problem for the stability and quality of drinking water production, especially in places that depend on groundwater for drinking water. Bioremediation is suggested as a valuable strategy for removing BAM from groundwater by deploying dedicated BAM-degrading bacteria in DWTP sand filters. Only a few bacterial strains with the capability to degrade BAM have been isolated, and of these, only three isolates belonging to the Aminobacter genus are able to mineralise BAM. Considerable effort has been made to elucidate degradation pathways, kinetics and degrader genes, and research has recently been presented on the application of strain Aminobacter sp. MSH1 for the purification of BAM-contaminated water. The aim of the present review was to provide insight into the issue of BAM contamination and to report on the current status and knowledge with regard to the application of microorganisms for purification of BAM-contaminated water resources. This paper discusses the prospects and challenges for bioaugmentation of DWTP sand filters with specific BAM-degrading bacteria and identifies relevant perspectives for future research.

Establishment of Bacterial Herbicide Degraders in a Rapid Sand Filter for Bioremediation of Phenoxypropionate-Polluted Groundwater.

In this study, we investigated the establishment of natural bacterial degraders in a sand filter treating groundwater contaminated with the phenoxypropionate herbicides (RS)-2-(4-chloro-2-methylphenoxy)propanoic acid (MCPP) and (RS)-2-(2,4-dichlorophenoxy)propanoic acid (DCPP) and the associated impurity/catabolite 4-chlorophenoxypropanoic acid (4-CPP). A pilot facility was set up in a contaminated landfill site. Anaerobic groundwater was pumped up and passed through an aeration basin and subsequently through a rapid sand filter, which is characterized by a short residence time of the water in the filter. For 3 months, the degradation of DCPP, MCPP, and 4-CPP in the sand filter increased to 15 to 30% of the inlet concentration. A significant selection for natural bacterial herbicide degraders also occurred in the sand filter. Using a most-probable-number (MPN) method, we found a steady increase in the number of culturable phenoxypropionate degraders, reaching approximately 5 × 10(5) degraders per g sand by the end of the study. Using a quantitative PCR targeting the two phenoxypropionate degradation genes, rdpA and sdpA, encoding stereospecific dioxygenases, a parallel increase was observed, but with the gene copy numbers being about 2 to 3 log units higher than the MPN. In general, the sdpA gene was more abundant than the rdpA gene, and the establishment of a significant population of bacteria harboring sdpA occurred faster than the establishment of an rdpA gene-carrying population. The identities of the specific herbicide degraders in the sand filter were assessed by Illumina MiSeq sequencing of 16S rRNA genes from sand filter samples and from selected MPN plate wells. We propose a list of potential degrader bacteria involved in herbicide degradation, including representatives belonging to the Comamonadaceae and Sphingomonadales.

Surface Colonization and Activity of the 2,6-Dichlorobenzamide (BAM) Degrading Aminobacter sp. Strain MSH1 at Macro- and Micropollutant BAM Concentrations.

Aminobacter sp. MSH1 uses the groundwater micropollutant 2,6-dichlorobenzamide (BAM) as a C and N source and is a potential catalyst for biotreatment of BAM-contaminated groundwater in filtration units of drinking water treatment plants (DWTPs). The oligotrophic environment of DWTPs including trace pollutant concentrations, and the high flow rates impose challenges for micropollutant biodegradation in DWTPs. To understand how trace BAM concentrations affect MSH1 surface colonization and BAM degrading activity, MSH1 was cultivated in flow channels fed continuously with BAM macro- and microconcentrations in a N- and C-limiting medium. At all BAM concentrations, MSH1 colonized the flow channel. BAM degradation efficiencies were concentration-dependent, ranging between 70 and 95%. Similarly, BAM concentration affected surface colonization, but at 100 µg/L BAM and lower, colonization was similar to that in systems without BAM, suggesting that assimilable organic carbon and nitrogen other than those supplied by BAM sustained colonization at BAM microconcentrations. Comparison of specific BAM degradation rates in flow channels and in cultures of suspended freshly grown cells indicated that starvation conditions in flow channels receiving BAM microconcentrations resulted into MSH1 biomasses with 10-100-times reduced BAM degrading activity and provided a kinetic model for predicting BAM degradation under continuous C and N starvation.

Protozoa graze on the 2,6-dichlorobenzamide (BAM)-degrading bacterium Aminobacter sp. MSH1 introduced into waterworks sand filters.

Groundwater contamination by pesticide residues often leads to the closure of drinking water wells, making the development of new techniques to remediate drinking water resources of considerable interest. Pesticide-degrading bacteria were recently added to a waterworks sand filter in an attempt to remediate pesticide-polluted drinking water. The density of the introduced bacteria, however, decreased rapidly, which was partly attributed to predation by protozoa in the sand filter. This study investigated the effects of indigenous sand filter protozoa on the population density and degradation efficiency of degrader bacteria introduced into sand from a waterworks sand filter. The 2,6-dichlorobenzamide (BAM)-degrading bacterium Aminobacter sp. MSH1 was used as a model organism. The introduction of MSH1 at high cell densities was followed by a >1000-fold increase in the protozoan population size and at the same time a 29 % reduction in Aminobacter cell numbers. The protozoan population in the systems that had MSH1 added at a lower density only increased 50-fold, and a decrease in Aminobacter numbers was not detectable. Furthermore, a reduction in the number of Aminobacter and in BAM degradation efficiency was seen in flow-through sand filter columns inoculated with MSH1 and fed BAM-contaminated water, when comparing sand columns containing the indigenous microbial filter community, i.e. containing protozoa, to columns with sterilised sand. These results suggest that degrader bacteria introduced into waterworks sand filters are adversely affected by grazing from the indigenous protozoa, reducing the size of the degrader population and the sand filter degradation efficiency.

Micro-flow-injection analysis (µFIA) immunoassay of herbicide residue 2,6-dichlorobenzamide ­ towards automated at-line monitoring using modular microfluidics.

As a part of developing new systems for continuously monitoring the presence of pesticides in groundwater, a microfluidic amperometric immunosensor was developed for detecting the herbicide residue 2,6-dichlorobenzamide (BAM) in water. A competitive immunosorbent assay served as the sensing mechanism and amperometry was applied for detection. Both the immunoreaction chip (IRC) and detection (D) unit are integrated on a modular microfluidic platform with in-built micro-flow-injection analysis (µFIA) function. The immunosorbent, immobilized in the channel of the IRC, was found to have high long-term stability and withstand many regeneration cycles, both of which are key requirements for systems utilized in continuous monitoring. The IRC was regenerated during 51 cycles in a heterogeneous competitive assay out of which 27 were without the analyte (the highest possible signal level) in order to assess the regeneration capability of the immunosorbent. Detection of BAM standard solutions was performed in the concentration range from 62.5 µg L(-1) to 0.0008 µg L(-1). Non-linear regression of the data using the four-parameter logistic equation generated a sigmoidal standard curve showing an IC50 value (concentration that reduces the signal by 50%) of 0.25 µg L(-1). The strongest signal variation is observed in the concentration range between 0.02 and 2.5 µg L(-1), which includes the 0.1 µg L(-1) threshold limit set by the European Commission for BAM in drinking water. The presented results demonstrate the potential of the constructed µFIA immunosensor as an at-line monitoring system for controlling the quality of ground water supply.