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Deep-rooted plants can obtain water and nutrients from the subsoil, making them resilient to climatic changes. Plant growth and health may depend on interactions with root-associated bacteria, but the composition and assembly dynamics of deep root-associated bacterial communities are unknown, as are their ability to supply plants with nitrogen (N). Here, we investigated the root-associated communities of the three deep-rooted perennial crops, lucerne (Medicago sativa), intermediate wheatgrass (Thinopyrum intermedium), and rosinweed (Silphium integrifolium), grown in 4 m tall RootTowers, under semi-natural conditions. Across the plant species, higher bacterial abundance and lower diversity were found in the root-associated communities compared to the bulk soil communities. The deep root-associated communities were enriched in the genera Pseudarthrobacter, Pseudomonas, Rhizobium and Streptomyces, genera found to harbor a wide variety of bacterial species expressing plant beneficial traits. The composition of the deep root-associated bacterial communities were plant species specific, and clearly distinct from the shallow communities. Additionally, the deep root-associated communities comprised primarily amplicon sequence variants (ASVs) that were omnipresent in the bulk soil, and to a limited extent ASVs that could have been transported from the topsoil or potentially from the seed. Abundances of genes involved in N-cycling: amoA, nifH, nirK, nirS and nosZ showed plant species specific patterns, and indicated that intermediate wheatgrass and lucerne recruit N-fixing bacteria even at 3 m depth for N supply. This work provides the first steps toward understanding plant-microbe interactions of deep-rooted crops, which are important for evaluating these crops for use in future sustainable cropping systems.

Soil contamination with trace elements is a major global threat to soil quality and ecosystem functioning. Its impact on soil microorganisms and the critical processes they undergo remains a challenge to predict under natural field conditions. Soil remediation aims to not only reduce contaminant toxicity in soil, but also to improve overall soil quality. Yet, few studies investigate microbial recovery following soil remediation, particularly when employing harsher remediation technologies such as soil washing with chemical ligands. To better predict the response and recovery of microbial communities in these complex soil systems, a comprehensive understanding of the interplay between soil-microbe-contaminant is needed. This can be achieved by using an integrative multi-disciplinary approach that combines soil chemistry, microbial ecology and multivariate statistics. To this end, this PhD thesis aims to infer specific effects of multi-element contaminatio n on soil bacterial communities in the field and to assess the recovery of the soil microbiome after remediation. Additionally, we evaluated the ability of the soil microbiome to function as an ecological indicator of soil quality before and after remediation. Chromated copper arsenate (CCA) contaminated sites, a by-product of the wood impregnation industry, were used as a multi-element contamination model system of global relevance. First, in Manuscript I, we characterized the chemical composition of soil at a heterogeneous CCA contaminated field site and established a contamination gradient with highly variable soil edaphic factors. The distribution of Cr, Cu and As amongst different soil solid phases was assessed using an advanced sequential extraction method called CISED – Chemometric Identification of Substrates and Element Distributions. This study demonstrated that, even after long-term ageing, Cu and As were associated with readily available phases in soil, constituting the highest potential ecological risk.

Arsenic (As) is a ubiquitous toxic element adversely affecting human health. Microbe-mediated cycling of As is largely mediated by detoxification and energy metabolism in microorganisms. We here report the development of a novel high-throughput qPCR (HT-qPCR) chip (AsChip) for comprehensive profiling of genes involved in microbial As cycling (here collectively termed "As genes"). AsChip contained 81 primer sets targeting 19 As genes and the 16S rRNA gene as a reference gene. Gene amplicon sequencing showed high identity (>96%) of newly designed primers corresponding to their targets. AsChip displayed high sensitivity (plasmid template serial dilution test; r = -0.99), with more than 96% of all PCR assays yielding true positive signals. R 2 coefficients for standard curves and PCR amplification efficiencies averaged 0.98 and 0.99, respectively. A high correlation between C T values obtained by AsChip and conventional qPCR was obtained (r = 0.962, P < 0.001). Finally, we successfully applied AsChip on soil samples from a chromium-copper-arsenic-contaminated field site and identified diverse As genes with total abundance average of 0.4 As gene copies per 16S rRNA. Our results indicate that AsChip constitutes a robust tool for comprehensive quantitative profiling of As genes in environmental samples.

Human-induced metal contaminations are distributed worldwide, due to manifold anthropogenic activities, like mining, agriculture and other industries. Under these contamination sources, CCA-contaminated soil sites are representing multi-metal pollutions, which involve high concentrations of Cr, Cu and As. These metals can lead to lethal and carcinogenic effects in humans, and further can severely affect the different components of the environment, like soil, groundwater, plants or microorganism. Additionally, CCA-contaminated sites pose a serious risk of co-selection for microbial antibiotic resistance, due to the toxicant-induced co-selective pressure on soil microorganism. The objective of this study was to detect pollution-induced selection for metal tolerant soil bacteria, originating from a CCA-contaminated site located in Denmark. The detection of metal tolerance was observed by the different sensitivities of the bacteria to an increasing metal contamination degree. Additionally, co-selection for tetracycline tolerance, induced by the pre-existing metal pollution, was tested. For investigation of bacterial adaptation to toxicant exposure, the Pollution-Induced Community Tolerance (PICT) assay was considered, which has been shown to be a robust and sensitive approach for elucidating field effects of toxicants, like metals, on soil bacterial communities. The PICT assay is based on the hypothesis that the selection for tolerant bacteria already took place on-site, and hence can be detected in the lab, during a short, second time toxicant exposure. The quantification of the PICT was conducted by the [3H]leucine incorporation assay, which involves a metabolic process that is proportional to the bacterial growth rate, and thus reveals the response of the soil bacterial community to the short-time toxicant exposure. The investigated soil samples of the CCA-contaminated site were tested for selection of As(III) and Cu(II) tolerance and co-selection for tetracy