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It is accepted that usage of antimicrobials (AMs) in food animals causes the emergence and spread of antimicrobial resistance (AMR) in this sector, while also contributing to the burden of AMR in humans. Curbing the increasing occurrence of AMR in food animals requires in-depth knowledge of the quantitative relationship between antimicrobial usage (AMU) and AMR to achieve desired resistance reductions from interventions targeting AMU. In the observational study, the relationships between lifetime AMU in 83 finisher batches from Danish farms and the AMR gene abundances of seven antimicrobial classes in their gut microbiomes were quantified using multi-variable linear regression models. These relationships and the national lifetime AMU in pigs were included in the predictive modelling that allowed for testing of scenarios with changed lifetime AMU for finishers produced in Denmark in 2014. A total of 50 farms from the observational study were included in validating the observational study and the predictive modelling. The results from the observational study showed that the relationship was linear, and that the parenteral usage of AMs had a high effect on specific AM-classes of resistance, whereas the peroral usage had a lower but broader effect on several classes. Three different scenarios of changed lifetime AMU were simulated in the predictive modelling. When all tetracycline usage ceased, the predicted interval reductions of aminoglycoside, lincosamide and tetracycline resistance were 4–42 %, 0–8 % and 9–18 %, respectively. When the peroral tetracycline usage of the 10 % highest users was replaced with peroral macrolide usage, the tetracycline resistance fell by 1–2 % and the macrolide and MLSb resistance increased by 5–8 %. When all extended-spectrum penicillin usage was replaced with parenteral lincosamide usage, the beta-lactam resistance fell by 2–7 %, but the lincosamide usage and resistance increased by 194 % and 10–45 %, respectively. The external validation provided results within the 95 % CI of the predictive modelling outcome at national level, while the external validation at farm level was less accurate. In conclusion, interventions targeting AMU will reduce AMR abundance, though differently depending on the targeted AM-class and provided the reduction of one AM-class usage is not replaced with usage of another AM-class. Predicting several classes of AMR gene abundance simultaneously will support stakeholders when deciding on interventions targeting AMU in the finisher production to avoid adverse and unforeseen effects on the AMR abundance. This study provides a sound predictive modelling framework for further development, including the dynamics of AMU on AMR in finishers at national level.

Rapid sand filtration is essential at most waterworks that treat anaerobic groundwater. Often the filtration depends on microbiological processes, but the microbial communities of the filters are largely unknown. We determined the prokaryotic community structures of 11 waterworks receiving groundwater from different geological settings by 16S rRNA gene-based 454 pyrosequencing and explored their relationships to filtration technology and raw water chemistry. Most of the variation in microbial diversity observed between different waterworks sand filters could be explained by the geochemistry of the inlet water. In addition, our findings suggested four features of particular interest: (1) Nitrospira dominated over Nitrobacter at all waterworks, suggesting that Nitrospira is a key nitrifying bacterium in groundwater-treating sand filters. (2) Hyphomicrobiaceae species were abundant at all waterworks, where they may be involved in manganese oxidation. (3) Six of 11 waterworks had significant concentrations of methane in their raw water and very high abundance of the methanotrophic Methylococcaceae. (4) The iron-oxidizing bacteria Gallionella was present at all waterworks suggesting that biological iron oxidation is occurring in addition to abiotic iron oxidation. Elucidation of key members of the microbial community in groundwater-treating sand filters has practical potential, for example, when methods are needed to improve filter function.

ObjectivesReliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring.MethodsWe evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing.ResultsMetagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment.ConclusionsWe present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.

BAM (2,6-dichlorobenzamide) is a metabolite of the pesticide dichlobenil. Naturally occurring bacteria that can utilize BAM are rare. Often the compound cannot be degraded before it reaches the groundwater and therefore it poses a serious threat to drinking water supplies. The bacterial strain Aminobacter MSH1 is a BAM degrader and therefore a potential candidate to be amended to sand filters in waterworks to remediate BAM polluted drinking water. A common problem in bioremediation is that bacteria artificially introduced into new diverse environments often thrive poorly, which is even more unfortunate because biologically diverse environments may ensure a more complete decomposition. To test the bioaugmentative potential of MSH1, we used a serial dilution approach to construct microcosms with different biological diversity. Subsequently, we amended Aminobacter MSH1 to the microcosms in two final concentrations; i.e. 10(5) cells mL(-1) and 10(7) cells mL(-1). We anticipated that BAM degradation would be most efficient at "intermediate diversities" as low diversity would counteract decomposition because of incomplete decomposition of metabolites and high diversity would be detrimental because of eradication of Aminobacter MSH1. This hypothesis was only confirmed when Aminobacter MSH1 was amended in concentrations of 10(5) cells mL(-1). Our findings suggest that Aminobacter MSH1 is a very promising bioremediator at several diversity levels.

Bioremediation of pesticide-polluted soil may be more efficient using mixed fungal-bacterial cultures rather than the individual strains alone. This may be due to cooperative catabolism, where the first organism transforms the pollutant to products which are then used by the second organism. In addition, fungal hyphae may function as transport vectors for bacteria, thereby facilitating a more effective spreading of degrader organisms in the soil. A more rapid mineralization of the phenylurea herbicide diuron was found in sand with added microbial consortia consisting of both degrading bacteria and fungi. Facilitated transport of bacteria by fungal hyphae was demonstrated using a system where herbicide-spiked sand was separated from the consortium by a layer of sterile glass beads. Several fungal-bacterial consortia were investigated by combining different diuron-degrading bacteria (Sphingomonas sp. SRS2, Variovorax sp. SRS16, and Arthrobacter globiformis D47) and fungi (Mortierella sp. LEJ702 and LEJ703). The fastest mineralization of (14)C-labeled diuron was seen in the consortium consisting of Mortierella LEJ702, Variovorax SRS16, and A. globiformis D47, as measured by evolved (14)CO2. In addition, the production of diuron metabolites by this consortium was minimal. Analyses of 16S rDNA suggested that bacteria were transported more efficiently by LEJ702 than by LEJ703. Finally, it was determined that the fungal growth differed for LEJ702 and LEJ703 in the three-member consortia. This study demonstrates new possibilities for applying efficient fungal-bacterial consortia for bioremediation of polluted soil.

The Aminobacter sp. strain MSH1 has potential for pesticide bioremediation because it degrades the herbicide metabolite 2,6-dichlorobenzamide (BAM). Production of the BAM-degrading bacterium using aerobic bioreactor fermentation was investigated. A mineral salt medium limited for carbon and with an element composition similar to the strain was generated. The optimal pH and temperature for strain growth were determined using shaker flasks and verified in bioreactors. Glucose, fructose, and glycerol were suitable carbon sources for MSH1 (μ = 0.1 h(-1)); slower growth was observed on succinate and acetic acid (μ = 0.01 h(-1)). Standard conditions for growth of the MSH1 strain were defined at pH 7 and 25 °C, with glucose as the carbon source. In bioreactors (1 and 5 L), the specific growth rate of MSH1 increased from μ = 0.1 h(-1) on traditional mineral salt medium to μ = 0.18 h(-1) on the optimized mineral salt medium. The biomass yield under standard conditions was 0.47 g dry weight biomass/g glucose consumed. An investigation of the catabolic capacity of MSH1 cells harvested in exponential and stationary growth phases showed a degradation activity per cell of about 3 × 10(-9) μg BAM h(-1). Thus, fast, efficient, large-scale production of herbicide-degrading Aminobacter was possible, bringing the use of this bacterium in bioaugmentation field remediation closer to reality.

Introduction of specific degrading microorganisms into polluted soil or aquifers is a promising remediation technology provided that the organisms survive and spread in the environment. We suggest that consortia, rather than single strains, may be better suited to overcome these challenges. Here we introduced a fungal-bacterial consortium consisting of Mortierella sp. LEJ702 and the 2,6-dichlorobenzamide (BAM)-degrading Aminobacter sp. MSH1 into small sand columns. A more rapid mineralisation of BAM was obtained by the consortium compared to MSH1 alone especially at lower moisture contents. Results from quantitative real-time polymerase chain reaction (qPCR) demonstrated better spreading of Aminobacter when Mortierella was present suggesting that fungal hyphae may stimulate bacterial dispersal. Extraction and analysis of BAM indicated that translocation of the compound was also affected by the fungal hyphae in the sand. This suggests that fungal-bacterial consortia are promising for successful bioremediation of pesticide contamination.