Needles in haystacks: monitoring the potential escape of bioaerosolised antibacterial resistance genes from wastewater treatment plants with air and phyllosphere sampling.

Wastewater treatment plants are well-known point sources of emissions of antibacterial resistance genes (ARGs) into the environment. Although most work to date has focused on ARG dispersal via effluent, aerial dispersal in bioaerosols is a poorly understood, but likely important vector for ARG dispersal. Recent evidence suggests that ARG profiles of the conifer needle phyllosphere could be used to measure bioaerosol dispersal from anthropogenic sources. Here, we assessed airborne dispersal of ARGs from wastewater treatment plants in Wales, UK and Quebec, Canada, using conifer needles as passive bioaerosol monitors. ARG profiles of wastewater were compared to those of conifer phyllosphere using high-throughput qPCR. ARG richness was significantly lower in conifer phyllosphere samples than wastewater samples, though no differences were observed across the dispersal gradients. Mean copy number of ARGs followed a similar trend. ARG profiles showed limited, but consistent patterns with increasing distance from wastewater treatment plants, but these did not align with those of wastewater samples. For example, proportional abundance of aminoglycosides decreased over the dispersal gradient in Wales, whereas mobile genetic elements showed the inverse relationship. In summary, while distinct ARG profiles exist along dispersal gradients, links to those of wastewater were not apparent.

Conifer Needle Phyllosphere as a Potential Passive Monitor of Bioaerosolised Antibiotic Resistance Genes.

Monitoring antibiotic resistance genes (ARGs) is vital to the One Health approach to tackling the antibiotic resistance crisis. It has been suggested that conifer needles can be used as passive bioaerosol samplers. Here, the use of conifer needles as biomonitors of ARGs in bioaerosols was assessed as a proof-of-concept. Needles were collected from trees surrounding pig farms, villages, and forest sites in Québec, Canada. Needles were homogenised and DNA was extracted. Results of qPCR analyses showed biomass estimates were consistent across samples. Number and quantity of ARGs was significantly lower in forest sites when compared to the farm and village, comprising a distinct resistome. Consistent with previous findings, the most common ARGs were tetracyclines and sulfonamides, which were found close to agricultural activities. Although results were limited, there is great potential for using the conifer phyllosphere as a passive bioaerosol sampler. This method represents an accessible way to promote ARG surveillance over long distances from point sources.

Antimicrobial Resistance in the Environment: Towards Elucidating the Roles of Bioaerosols in Transmission and Detection of Antibacterial Resistance Genes.

Antimicrobial resistance (AMR) is continuing to grow across the world. Though often thought of as a mostly public health issue, AMR is also a major agricultural and environmental problem. As such, many researchers refer to it as the preeminent One Health issue. Aerial transport of antimicrobial-resistant bacteria via bioaerosols is still poorly understood. Recent work has highlighted the presence of antibiotic resistance genes in bioaerosols. Emissions of AMR bacteria and genes have been detected from various sources, including wastewater treatment plants, hospitals, and agricultural practices; however, their impacts on the broader environment are poorly understood. Contextualizing the roles of bioaerosols in the dissemination of AMR necessitates a multidisciplinary approach. Environmental factors, industrial and medical practices, as well as ecological principles influence the aerial dissemination of resistant bacteria. This article introduces an ongoing project assessing the presence and fate of AMR in bioaerosols across Canada. Its various sub-studies include the assessment of the emissions of antibiotic resistance genes from many agricultural practices, their long-distance transport, new integrative methods of assessment, and the creation of dissemination models over short and long distances. Results from sub-studies are beginning to be published. Consequently, this paper explains the background behind the development of the various sub-studies and highlight their shared aspects.

Shifts in Soil Structure, Biological, and Functional Diversity Under Long-Term Carbon Deprivation.

Soil organic matter is composed of a variety of carbon (C) forms. However, not all forms are equally accessible to soil microorganisms. Deprivation of C inputs will cause changes in the physical and microbial community structures of soils; yet the trajectories of such changes are not clear. We assessed microbial communities using phospholipid fatty acid profiling, metabarcoding, CO2 emissions, and functional gene microarrays in a decade-long C deprivation field experiment. We also assessed changes in a range of soil physicochemical properties, including using X-ray Computed Tomography imaging to assess differences in soil structure. Two sets of soils were deprived of C inputs by removing plant inputs for 10 years and 1 year, respectively. We found a reduction in diversity measures, after 10 years of C deprivation, which was unexpected based on previous research. Fungi appeared to be most impacted, likely due to competition for scarce resources after exhausting the available plant material. This suggestion was supported by evidence of bioindicator taxa in non-vegetated soils that may directly compete with or consume fungi. There was also a reduction in copies of most functional genes after 10 years of C deprivation, though gene copies increased for phytase and some genes involved in decomposing recalcitrant C and methanogenesis. Additionally, soils under C deprivation displayed expected reductions in pH, organic C, nitrogen, and biomass as well as reduced mean pore size, especially in larger pores. However, pore connectivity increased after 10 years of C deprivation contrary to expectations. Our results highlight concurrent collapse of soil structure and biodiversity following long-term C deprivation. Overall, this study shows the negative trajectory of continuous C deprivation and loss of organic matter on a wide range of soil quality indicators and microorganisms.

Manipulation of the soil microbiome regulates the colonization of plants by arbuscular mycorrhizal fungi.

Arbuscular mycorrhizal fungi (AMF) are important symbionts of many plant species, facilitating the acquisition of soil nutrients by roots. We hypothesized that AMF root colonization is strongly influenced by the composition of the soil microbiome. Here, we evaluated mycorrhizal colonization of two plants, the grass Urochloa brizantha (Brachiaria) and the legume Crotalaria juncea (Crotalaria). These were cultivated in the same soil but hosting eight distinct microbiomes: natural soil (i); soil exposed to heat treatments for 1 h at 50 ºC (ii), 80 ºC (iii), or 100 ºC (iv); sterilized soil by autoclaving (AS) followed by re-inoculation of dilutions of the natural soil community at 10-1 (v), 10-3 (vi), and 10-6 (vii); and AS without re-inoculation (viii). Microbial diversity (bacteria and fungi) was assessed through 16S rDNA and ITS1 metabarcoding, respectively, and the soil acid phosphatase activity (APASE) was measured. Sequencing results showed the formation of distinct microbial communities according to the soil manipulations, which also correlated with the decline of APASE. Subsequently, seedlings of Brachiaria and Crotalaria were grown in those soils inoculated separately with three AMF (Acaulospora colombiana, Rhizophagus clarus, and Dentiscutata heterogama) which were compared to an AMF-free control treatment. Brachiaria showed higher colonization in natural soil when compared to the microbial community manipulations, regardless of the AMF species inoculated. In contrast, two mycorrhiza species were able to colonize Crotalaria under modified microbial communities at similar rates to natural soil. Furthermore, Brachiaria showed a possible inverse relationship between APASE and mycorrhization, but this trend was absent for Crotalaria. We conclude that mycorrhizal root colonization and soil acid phosphatase activity were associated with the structure of the soil microbiome, depending on the plant species evaluated.

Beyond Taxonomic Identification: Integration of Ecological Responses to a Soil Bacterial 16S rRNA Gene Database.

High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalizing syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterize taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from survey metadata. Specifically, we modeled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on both the shape of landscape scale pH-abundance responses, and pH optima (pH at which OTU abundance is maximal). We identify that most of the soil OTUs examined exhibited a non-flat relationship with soil pH. Further, the pH optima could not be generalized by broad taxonomy, highlighting the need for tools and databases synthesizing ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER/), and flat files are made available for use in bioinformatic pipelines. The further development of advanced informatics infrastructures incorporating modeled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.

Plant and soil communities are associated with the response of soil water repellency to environmental stress.

A warming climate and expected changes in average and extreme rainfall emphasise the importance of understanding how the land surface routes and stores surface water. The availability and movement of water within an ecosystem is a fundamental control on biological and geophysical activity, and influences many climatic feedbacks. A key phenomenon influencing water infiltration into the land surface is soil hydrophobicity, or water repellency. Despite repellency dictating the speed, volume and pattern of water infiltration, there is still major uncertainty over whether this critical hydrological process is biologically or physicochemically controlled. Here we show that soil water repellency is likely driven by changes in the plant and soil microbial communities in response to environmental stressors. We carried out a field survey in the summers of 2013 to 2016 in a variety of temperate habitats ranging across arable, grassland, forest and bog sites. We found that moderate to extreme repellency occurs in 68% of soils at a national scale in temperate ecosystems, with 92% showing some repellency. Taking a systems approach, we show that a wetter climate and low nutrient availability alter plant, bacterial and fungal community structure, which in turn are associated with increased soil water repellency across a large-scale gradient of soil, vegetation and land-use. The stress tolerance of the plant community and associated changes in soil microbial communities were more closely linked to changes in repellency than soil physicochemical properties. Our results indicate that there are consistent responses to diverse ecosystem stresses that will impact plant and microbial community composition, soil properties, and hydrological behaviour. We suggest that the ability of a biological community to induce such hydrological responses will influence the resilience of the whole ecosystem to environmental stress. This highlights the crucial role of above-belowground interactions in mediating climatic feedbacks and dictating ecosystem health.

Divergent national-scale trends of microbial and animal biodiversity revealed across diverse temperate soil ecosystems.

Soil biota accounts for ~25% of global biodiversity and is vital to nutrient cycling and primary production. There is growing momentum to study total belowground biodiversity across large ecological scales to understand how habitat and soil properties shape belowground communities. Microbial and animal components of belowground communities follow divergent responses to soil properties and land use intensification; however, it is unclear whether this extends across heterogeneous ecosystems. Here, a national-scale metabarcoding analysis of 436 locations across 7 different temperate ecosystems shows that belowground animal and microbial (bacteria, archaea, fungi, and protists) richness follow divergent trends, whereas ß-diversity does not. Animal richness is governed by intensive land use and unaffected by soil properties, while microbial richness was driven by environmental properties across land uses. Our findings demonstrate that established divergent patterns of belowground microbial and animal diversity are consistent across heterogeneous land uses and are detectable using a standardised metabarcoding approach.