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The ammonia monooxygenase (AMO) is a key enzyme in ammonia oxidising archaea, which are abundant and ubiquitous in soil environments. The AMO belongs to the copper-containing membrane monooxygenase (CuMMO) enzyme superfamily, which also contains particulate methane monooxygenase (pMMO). Enzymes in the CuMMO superfamily are promiscuous, which results in co-oxidation of alternative substrates. The phylogenetic and structural similarity between the pMMO and the archaeal AMO is well-established, but there is surprisingly little information on the influence of methane and methanol on the archaeal AMO and terrestrial nitrification. The aim of this study was to examine the effects of methane and methanol on the soil ammonia oxidising archaeon 'Ca. Nitrosocosmicus franklandus C13'. We demonstrate that both methane and methanol are competitive inhibitors of the archaeal AMO. The inhibition constants (K

Ammonia-oxidizing archaea (AOA) and bacteria (AOB) perform key steps in the global nitrogen cycle, the oxidation of ammonia to nitrite. While the ammonia oxidation pathway is well characterized in AOB, many knowledge gaps remain about the metabolism of AOA. Hydroxylamine is an intermediate in both AOB and AOA, but homologues of hydroxylamine dehydrogenase (HAO), catalyzing bacterial hydroxylamine oxidation, are absent in AOA. Hydrazine is a substrate for bacterial HAO, while phenylhydrazine is a suicide inhibitor of HAO. Here, we examine the effect of hydrazines in AOA to gain insights into the archaeal ammonia oxidation pathway. We show that hydrazine is both a substrate and an inhibitor for AOA and that phenylhydrazine irreversibly inhibits archaeal hydroxylamine oxidation. Both hydrazine and phenylhydrazine interfered with ammonia and hydroxylamine oxidation in AOA. Furthermore, the AOA "

Additional file 6: Supplementary Figure 6. Denaturing gel gradient electrophoresis (DGGE) showing bacterial 16S rRNA gene diversity across the 12 fractions generated for stable isotope probing for the 13C unplanted soil controls (N = 3). Primers indicated in Supplementary Table 6.

Additional file 3: Supplementary Figure 3. Denaturing gel gradient electrophoresis (DGGE) showing archaeal 16S rRNA gene diversity across the 12 fractions generated for stable isotope probing for the rhizosphere associated with one 12C control (left) and 13C labelled (right) plant. Primers indicated in Supplementary Table 6.

Additional file 4: Supplementary Figure 4. Quantitative PCR against the fungal 18S rRNA gene to test for 13C labelling of the fungal community across fractions form the stable isotope probing. Graphs shows the percent of total 18S rRNA genes found within each of the 12 fractions for each plant (plotted as buoyant densities for that fraction in g / ml− 1) for 12C control and 13C labelled wheat plants from rhizosphere (A) and endosphere compartments (B) (N = 3).

Additional file 2: Supplementary Figure 2. Denaturing gel gradient electrophoresis (DGGE) showing bacterial 16S rRNA gene diversity across the 12 fractions generated for stable isotope probing for the rhizosphere associated with the 12C control (top) and 13C labelled (top) plant (N = 3). Primers indicated in Supplementary Table 6.

“Candidatus Nitrosocosmicus franklandus” C13 is an ammonia-oxidizing archaeon (AOA) isolated from soil. Its complete genome is 2.84 Mb and possesses predicted AOA metabolic pathways for energy generation and carbon dioxide fixation but no typical surface layer (S-layer) proteins, only one ammonium transporter, and divergent A-type ATP synthase genes.

Nutritional immunity describes the host-driven manipulation of essential micronutrients, including iron, zinc and manganese. To withstand nutritional immunity and proliferate within their hosts, pathogenic microbes must express efficient micronutrient uptake and homeostatic systems. Here we have elucidated the pathway of cellular zinc assimilation in the major human fungal pathogen Candida albicans. Bioinformatics analysis identified nine putative zinc transporters: four cytoplasmic-import Zip proteins (Zrt1, Zrt2, Zrt3 and orf19.5428) and five cytoplasmic-export ZnT proteins (orf19.1536/Zrc1, orf19.3874, orf19.3769, orf19.3132 and orf19.52). Only Zrt1 and Zrt2 are predicted to localise to the plasma membrane and here we demonstrate that Zrt2 is essential for C. albicans zinc uptake and growth at acidic pH. In contrast, ZRT1 expression was found to be highly pH-dependent and could support growth of the ZRT2-null strain at pH 7 and above. This regulatory paradigm is analogous to the distantly related pathogenic mould, Aspergillus fumigatus, suggesting that pH-adaptation of zinc transport may be conserved in fungi and we propose that environmental pH has shaped the evolution of zinc import systems in fungi. Deletion of C. albicans ZRT2 reduced kidney fungal burden in wild type, but not in mice lacking the zinc-chelating antimicrobial protein calprotectin. Inhibition of zrt2Δ growth by neutrophil extracellular traps was calprotectin-dependent. This suggests that, within the kidney, C. albicans growth is determined by pathogen-Zrt2 and host-calprotectin. As well as serving as an essential micronutrient, zinc can also be highly toxic and we show that C. albicans deals with this potential threat by rapidly compartmentalising zinc within vesicular stores called zincosomes. In order to understand mechanistically how this process occurs, we created deletion mutants of all five ZnT-type transporters in C. albicans. Here we show that, unlike in Saccharomyces cerevisiae, C. albicans Zrc1 mediates zinc tolerance via zincosomal zinc compartmentalisation. This novel transporter was also essential for virulence and liver colonisation in vivo. In summary, we show that zinc homeostasis in a major human fungal pathogen is a multi-stage process initiated by Zrt1/Zrt2-cellular import, followed by Zrc1-dependent intracellular compartmentalisation., Author summary All living organisms must secure certain trace metals such as iron and zinc in their diets. For the microbes that infect us, the source of these micronutrients is the tissues of their host. However, mammals have developed sophisticated mechanisms to manipulate microbial access to trace metals–a process called nutritional immunity. Therefore, successful pathogenic microorganisms must have evolved mechanisms to counteract nutritional immunity and acquire micronutrients in order to grow within their hosts and cause disease. This struggle for micronutrients represents a key host-pathogen battleground. In this study we demonstrate how the major human fungal pathogen, Candida albicans, acquires and stores zinc from its environment. We find that the mechanistic basis of zinc uptake is highly dependent on the acidity of the surrounding environment. Interestingly, this pH-dependence appears conserved in the fungal kingdom and we propose a potential framework for the evolution of zinc uptake in extant fungal species. Moreover, following cellular assimilation, C. albicans shuttles this potentially toxic transition metal into subcellular compartments called zincosomes. We also show that both zinc uptake and compartmentalisation are critical for C. albicans growth, both under laboratory conditions and in experimental models of invasive candidiasis.

Pathogenic microorganisms often face acute micronutrient limitation during infection due to the action of host-mediated nutritional immunity. The human fungal pathogen Candida albicans is polymorphic and its morphological plasticity is one of its most widely recognized pathogenicity attributes. Here we investigated the effect of zinc, iron, manganese, and copper limitation on C. albicans morphology. Restriction of zinc specifically resulted in the formation of enlarged, spherical yeasts, a phenotype which we term Goliath cells. This cellular response to zinc restriction was conserved in C. albicans, C. dubliniensis and C. tropicalis, but not in C. parapsilosis, C. lusitaniae or Debaryomyces hansenii, suggesting that it may have emerged in the last common ancestor of these related pathogenic species. Cell wall analysis revealed proportionally more chitin exposure on the Goliath cell surface. Importantly, these cells were hyper-adherent, suggesting a possible role in pathogenicity. Interestingly, the zincophore-encoding gene PRA1 was expressed by Goliath cells in zinc limited media and lack of Pra1 inhibited both cellular enlargement and adhesion. Goliath cells represent a further layer of Candida phenotypic plasticity.

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Additional file 5: Supplementary Figure 5. Endosphere stable isotope probing data. A Denaturing gel gradient electrophoresis (DGGE) showing bacterial 16S rRNA gene diversity across the 12 fractions generated for stable isotope probing for the endosphere associated with three 12C control (top) and 13C labelled (bottom) plants. These gels show a shift in the bacterial community towards the heavy fraction of 13C labelled plants. B Bars show the relative abundance of each bacterial group within the pooled sequenced 12C heavy, 12C light, 13C heavy and 13C light fractions (N = 3), for two separate sequencing runs on the same samples (old & new). C Principle coordinates analysis (PCoA) on bray cutis dissimilarities for the endosphere 12C heavy (orange/circle), 12C light (green/triangle), 13C heavy (blue/square) and 13C light (purple/cross) fractions (N = 3).

Additional file 1: Supplementary Figure 1. Denaturing gel gradient electrophoresis (DGGE) showing archaeal 16S rRNA gene (A, B) or amoA (C, D) diversity across the bulk soil, rhizosphere and endosphere of wheat grown under laboratory conditions in agricultural soil (A, C) or Levington F2 compost (B, D). Primers are indicated in the Supplementary Table 6.

Additional file 7: Supplementary Table 1. SIMPER outputs. Supplementary Table 2. Permanova results. Supplementary Table 3. Soil chemical properties. Supplementary Table 4. SIP fractions used for sequencing. Supplementary Table 5. DESeq2 outputs to identify root exudate utilisers in the rhizosphere. Supplementary Table 6. Primers. Supplementary Table 7. PCR Conditions for metabarcoding, qPCR & DGGE PCRs. Supplementary Table 8. Qiime 2 Dada2 settings. Supplementary Table 9. Qiime2 taxonomy-based filtering stats. Supplementary Table 10. DESeq2 output identifying CO2-fixing autotrophs from unplanted soil. Supplementary Table 11. DESeq2 outputs stem elongation field grown- Significantly differentially abundant bacterial taxa. Supplementary Table 12. DESeq2 outputs (all pot grown and stem elongation)- Significantly differentially abundant bacteria. Supplementary Table 13. DESeq2 outputs senescent plants- Significantly differentially abundant taxa. Supplementary Table 14. DESeq2 outputs stem elongation/senescent plants- Significantly differentially abundant bacterial taxa. Supplementary Table 15. DESeq2 outputs Significantly differentially abundant fungal taxa 01. Supplementary Table 16. DESeq2 outputs Significantly differentially abundant fungal taxa 02.

Additional file 5: Supplementary Figure 5. Endosphere stable isotope probing data. A Denaturing gel gradient electrophoresis (DGGE) showing bacterial 16S rRNA gene diversity across the 12 fractions generated for stable isotope probing for the endosphere associated with three 12C control (top) and 13C labelled (bottom) plants. These gels show a shift in the bacterial community towards the heavy fraction of 13C labelled plants. B Bars show the relative abundance of each bacterial group within the pooled sequenced 12C heavy, 12C light, 13C heavy and 13C light fractions (N = 3), for two separate sequencing runs on the same samples (old & new). C Principle coordinates analysis (PCoA) on bray cutis dissimilarities for the endosphere 12C heavy (orange/circle), 12C light (green/triangle), 13C heavy (blue/square) and 13C light (purple/cross) fractions (N = 3).

Additional file 7: Supplementary Table 1. SIMPER outputs. Supplementary Table 2. Permanova results. Supplementary Table 3. Soil chemical properties. Supplementary Table 4. SIP fractions used for sequencing. Supplementary Table 5. DESeq2 outputs to identify root exudate utilisers in the rhizosphere. Supplementary Table 6. Primers. Supplementary Table 7. PCR Conditions for metabarcoding, qPCR & DGGE PCRs. Supplementary Table 8. Qiime 2 Dada2 settings. Supplementary Table 9. Qiime2 taxonomy-based filtering stats. Supplementary Table 10. DESeq2 output identifying CO2-fixing autotrophs from unplanted soil. Supplementary Table 11. DESeq2 outputs stem elongation field grown- Significantly differentially abundant bacterial taxa. Supplementary Table 12. DESeq2 outputs (all pot grown and stem elongation)- Significantly differentially abundant bacteria. Supplementary Table 13. DESeq2 outputs senescent plants- Significantly differentially abundant taxa. Supplementary Table 14. DESeq2 outputs stem elongation/senescent plants- Significantly differentially abundant bacterial taxa. Supplementary Table 15. DESeq2 outputs Significantly differentially abundant fungal taxa 01. Supplementary Table 16. DESeq2 outputs Significantly differentially abundant fungal taxa 02.