Using metatranscriptomics to better understand the role of microbial nitrogen cycling in coastal sediment benthic flux denitrification efficiency.

Spatial and temporal variability in benthic flux denitrification efficiency occurs across Port Phillip Bay, Australia. Here, we assess the capacity for untargeted metatranscriptomics to resolve spatiotemporal differences in the microbial contribution to benthic nitrogen cycling. The most abundant sediment transcripts assembled were associated with the archaeal nitrifier Nitrosopumilus. In sediments close to external inputs of organic nitrogen, the dominant transcripts were associated with Nitrosopumilus nitric oxide nitrite reduction (nirK). The environmental conditions close to organic nitrogen inputs that select for increased transcription in Nitrosopumilus (amoCAB, nirK, nirS, nmo, hcp) additionally selected for increased transcription of bacterial nitrite reduction (nxrB) and transcripts associated with anammox (hzo) but not denitrification (bacterial nirS/nirk). In sediments that are more isolated from external inputs of organic nitrogen dominant transcripts were associated with nitrous oxide reduction (nosZ) and changes in nosZ transcript abundance were uncoupled from transcriptional profiles associated with archaeal nitrification. Coordinated transcription of coupled community-level nitrification-denitrification was not well supported by metatranscriptomics. In comparison, the abundance of archaeal nirK transcripts were site- and season-specific. This study indicates that the transcription of archaeal nirK in response to changing environmental conditions may be an important and overlooked feature of coastal sediment nitrogen cycling.

Temporal profiling resolves the drivers of microbial nitrogen cycling variability in coastal sediments.

Here we describe the potential for sediment microbial nitrogen-cycling gene (DNA) and activity (RNA) abundances to spatially resolve coastal areas impacted by seasonal variability in external nutrient inputs. Three sites were chosen within a nitrogen-limited embayment, Port Phillip Bay (PPB), Australia that reflect variability in both proximity to external nutrient inputs and the dominant form of available nitrogen. At three sediment depths (0-1; 1-5; 5-10 cm) across a 2 year study key genes involved in nitrification (archaeal amoA and bacterial ß-amoA), nitrite reduction (clade I nirS and cluster I nirK, archaeal nirK-a), anaerobic oxidation of ammonium (anammox 16S rRNA phylogenetic marker) and nitrogen fixation (nifH) were quantified. Sediments impacted by a dominance of organic nitrogen inputs were characterised at all time-points and to sediment depths of 10 cm by the highest transcript abundances of archaeal amoA and archaeal nirk-a. Proximity to a dominance of external nitrate inputs was associated with the highest transcript abundances of nirS which temporally co-varied with seasonal changes in sediment nitrate. Sediments isolated from external inputs displayed the greatest depth-specific decrease in quantifiable transcript abundances. In these isolated sediments bacterial ß-amoA transcripts were temporally associated with increased sediment ammonium levels. Across this nitrogen limited system variability in the abundance of bacterial ß-amoA, archaeal amoA, archaeal nirk-a or nirS transcripts from the sediment surface (0-1 and 5 cm) demonstrated a capacity to improve our ability to monitor coastal zones impacted by anthropogenic nitrogen inputs. Specifically, the spatial detection sensitivity of bacterial ß-amoA transcripts could be developed as a metric to determine spatiotemporal impacts of large external loading events. This temporal study demonstrates a capacity for microbial activity metrics to facilitate coastal management strategies through greater spatial resolution of areas impacted by external nutrient inputs.

Metabolomics approaches for the discrimination of disease suppressive soils for Rhizoctonia solani AG8 in cereal crops using 1H NMR and LC-MS.

The suppression of soilborne crop pathogens such as Rhizoctonia solani AG8 may offer a sustainable and enduring method for disease control, though soils with these properties are difficult to identify. In this study, we analysed the soil metabolic profiles of suppressive and non-suppressive soils over 2 years of cereal production. We collected bulk and rhizosphere soil at different cropping stages and subjected soil extracts to liquid chromatography-mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (1H NMR) analyses. Community analyses of suppressive and non-suppressive soils using principal component analyses and predictive modelling of LC-MS and NMR datasets respectively, revealed distinct biochemical profiles for the two soil types with clustering based on suppressiveness and cropping stage. NMR spectra revealed the suppressive soils to be more abundant in sugar molecules than non-suppressive soils, which were more abundant in lipids and terpenes. LC-MS features that were significantly more abundant in the suppressive soil were identified and assessed as potential biomarkers for disease suppression. The structures of a potential class of LC-MS biomarkers were elucidated using accurate mass data and MS fragmentation spectrum information. The most abundant compound found in association with suppressive soils was confirmed to be a macrocarpal, which is an antimicrobial secondary metabolite. Our study has demonstrated the utility of environmental metabolomics for the study of disease suppressive soils, resulting in the discovery of a macrocarpal biomarker for R. solani AG8 suppressive soil which can be further studied functionally in association with suppression pot trials and microbial isolation studies.

Primer selection influences abundance estimates of ammonia oxidizing archaea in coastal marine sediments.

Quantification of the α-subunit of ammonia monooxygenase (amoA) through PCR is an established technique for estimating the abundance of ammonia oxidizing archaea (AOA) in environmental samples. This study quantified AOA with two established primer sets in 1 cm increments from the sediment surface (0-1 cm) to a depth of 10 cm at two locations within Port Phillip Bay (PPB), Australia. Primer choice had a significant effect on within sample estimates of AOA with copy numbers ranging from 102 to 104 copies per ng DNA. Variation in AOA abundance patterns with increasing sediment depth were site and primer specific. Sequence mismatches between the primer binding region of the isolated amoA sequences from PPB and Nitrosopumilus maritimus SCM1 were identified and may explain the high variation identified between primer estimates. Our results highlight the need for testing multiple primer pairs that target different regions of the AOA amoA sequence prior to large-scale marine sediment environmental studies.

Comparative Metatranscriptomics of Wheat Rhizosphere Microbiomes in Disease Suppressive and Non-suppressive Soils for Rhizoctonia solani AG8.

The soilborne fungus Rhizoctonia solani anastomosis group (AG) 8 is a major pathogen of grain crops resulting in substantial production losses. In the absence of resistant cultivars of wheat or barley, a sustainable and enduring method for disease control may lie in the enhancement of biological disease suppression. Evidence of effective biological control of R. solani AG8 through disease suppression has been well documented at our study site in Avon, South Australia. A comparative metatranscriptomic approach was applied to assess the taxonomic and functional characteristics of the rhizosphere microbiome of wheat plants grown in adjacent fields which are suppressive and non-suppressive to the plant pathogen R. solani AG8. Analysis of 12 rhizosphere metatranscriptomes (six per field) was undertaken using two bioinformatic approaches involving unassembled and assembled reads. Differential expression analysis showed the dominant taxa in the rhizosphere based on mRNA annotation were Arthrobacter spp. and Pseudomonas spp. for non-suppressive samples and Stenotrophomonas spp. and Buttiauxella spp. for the suppressive samples. The assembled metatranscriptome analysis identified more differentially expressed genes than the unassembled analysis in the comparison of suppressive and non-suppressive samples. Suppressive samples showed greater expression of a polyketide cyclase, a terpenoid biosynthesis backbone gene (dxs) and many cold shock proteins (csp). Non-suppressive samples were characterised by greater expression of antibiotic genes such as non-heme chloroperoxidase (cpo) which is involved in pyrrolnitrin synthesis, and phenazine biosynthesis family protein F (phzF) and its transcriptional activator protein (phzR). A large number of genes involved in detoxifying reactive oxygen species (ROS) and superoxide radicals (sod, cat, ahp, bcp, gpx1, trx) were also expressed in the non-suppressive rhizosphere samples most likely in response to the infection of wheat roots by R. solani AG8. Together these results provide new insight into microbial gene expression in the rhizosphere of wheat in soils suppressive and non-suppressive to R. solani AG8. The approach taken and the genes involved in these functions provide direction for future studies to determine more precisely the molecular interplay of plant-microbe-pathogen interactions with the ultimate goal of the development of management options that promote beneficial rhizosphere microflora to reduce R. solani AG8 infection of crops.

Circular linkages between soil biodiversity, fertility and plant productivity are limited to topsoil at the continental scale.

The current theoretical framework suggests that tripartite positive feedback relationships between soil biodiversity, fertility and plant productivity are universal. However, empirical evidence for these relationships at the continental scale and across different soil depths is lacking. We investigate the continental-scale relationships between the diversity of microbial and invertebrate-based soil food webs, fertility and above-ground plant productivity at 289 sites and two soil depths, that is 0-10 and 20-30 cm, across Australia. Soil biodiversity, fertility and plant productivity are strongly positively related in surface soils. Conversely, in the deeper soil layer, the relationships between soil biodiversity, fertility and plant productivity weaken considerably, probably as a result of a reduction in biodiversity and fertility with depth. Further modeling suggested that strong positive associations among soil biodiversity-fertility and fertility-plant productivity are limited to the upper soil layer (0-10 cm), after accounting for key factors, such as distance from the equator, altitude, climate and physicochemical soil properties. These findings highlight the importance of surface soil biodiversity for soil fertility, and suggest that any loss of surface soil could potentially break the links between soil biodiversity-fertility and/or fertility-plant productivity, which can negatively impact nutrient cycling and food production, upon which future generations depend.

Nitrification Is a Primary Driver of Nitrous Oxide Production in Laboratory Microcosms from Different Land-Use Soils.

Most studies on soil N2O emissions have focused either on the quantifying of agricultural N2O fluxes or on the effect of environmental factors on N2O emissions. However, very limited information is available on how land-use will affect N2O production, and nitrifiers involved in N2O emissions in agricultural soil ecosystems. Therefore, this study aimed at evaluating the relative importance of nitrification and denitrification to N2O emissions from different land-use soils and identifying the potential underlying microbial mechanisms. A (15)N-tracing experiment was conducted under controlled laboratory conditions on four agricultural soils collected from different land-use. We measured N2O fluxes, nitrate ([Formula: see text]), and ammonium ([Formula: see text]) concentration and (15)N2O, (15)[Formula: see text], and (15)[Formula: see text] enrichment during the incubation. Quantitative PCR was used to quantify ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB). Our results showed that nitrification was the main contributor to N2O production in soils from sugarcane, dairy pasture and cereal cropping systems, while denitrification played a major role in N2O production in the vegetable soil under the experimental conditions. Nitrification contributed to 96.7% of the N2O emissions in sugarcane soil followed by 71.3% in the cereal cropping soil and 70.9% in the dairy pasture soil, while only around 20.0% of N2O was produced from nitrification in vegetable soil. The proportion of nitrified nitrogen as N2O (PN2O-value) varied across different soils, with the highest PN2O-value (0.26‰) found in the cereal cropping soil, which was around 10 times higher than that in other three systems. AOA were the abundant ammonia oxidizers, and were significantly correlated to N2O emitted from nitrification in the sugarcane soil, while AOB were significantly correlated with N2O emitted from nitrification in the cereal cropping soil. Our findings suggested that soil type and land-use might have strongly affected the relative contribution of nitrification and denitrification to N2O production from agricultural soils.

Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database.

BACKGROUND: Microbial inhabitants of soils are important to ecosystem and planetary functions, yet there are large gaps in our knowledge of their diversity and ecology. The 'Biomes of Australian Soil Environments' (BASE) project has generated a database of microbial diversity with associated metadata across extensive environmental gradients at continental scale. As the characterisation of microbes rapidly expands, the BASE database provides an evolving platform for interrogating and integrating microbial diversity and function. FINDINGS: BASE currently provides amplicon sequences and associated contextual data for over 900 sites encompassing all Australian states and territories, a wide variety of bioregions, vegetation and land-use types. Amplicons target bacteria, archaea and general and fungal-specific eukaryotes. The growing database will soon include metagenomics data. Data are provided in both raw sequence (FASTQ) and analysed OTU table formats and are accessed via the project's data portal, which provides a user-friendly search tool to quickly identify samples of interest. Processed data can be visually interrogated and intersected with other Australian diversity and environmental data using tools developed by the 'Atlas of Living Australia'. CONCLUSIONS: Developed within an open data framework, the BASE project is the first Australian soil microbial diversity database. The database will grow and link to other global efforts to explore microbial, plant, animal, and marine biodiversity. Its design and open access nature ensures that BASE will evolve as a valuable tool for documenting an often overlooked component of biodiversity and the many microbe-driven processes that are essential to sustain soil function and ecosystem services.

NMR metabolomics for soil analysis provide complementary, orthogonal data to MIR and traditional soil chemistry approaches--a land use study.

The present study was designed to analyse soils by different methodologies to determine the range of traits that could be investigated for the study of environmental soil samples. Proton nuclear magnetic resonance spectroscopy ((1) H NMR) was employed for metametabolomic analysis of soils from agricultural systems (managed) or from soils in a native state (remnant). The metabolomic methodologies employed (grinding and extraction with sonication) are capable of breaking up cell walls and so enabled characterisation of both extracellular and intracellular components of soil. Diffuse mid-infrared spectroscopy (MIR) data was obtained for the same sample sets, and in addition, elemental composition was determined by conventional laboratory chemical testing methods. Also investigated was the antibiotic activity of the soil extracts. Resilient or suppressive soils are valued in the agricultural setting as they convey disease resistance (against bacterial and fungal pathogens) to crop plants. In order to test if any such biological activity could be detected in the soils, the extracts were tested against the bacteria Bacillus subtilis. Several extracts showed strong growth inhibition against the bacteria with the most active clustered together in principle component analysis (PCA) of the metabolomic data. The study showed that the NMR metabolomic approach corresponds more accurately to land use and biochemical properties potentially associated with suppression, while MIR data correlated well to inorganic chemical analysis. Thus, the study demonstrates the utility in combining these spectroscopic methods for soil analysis.

Identification of genes and pathways related to phenol degradation in metagenomic libraries from petroleum refinery wastewater.

Two fosmid libraries, totaling 13,200 clones, were obtained from bioreactor sludge of petroleum refinery wastewater treatment system. The library screening based on PCR and biological activity assays revealed more than 400 positive clones for phenol degradation. From these, 100 clones were randomly selected for pyrosequencing in order to evaluate the genetic potential of the microorganisms present in wastewater treatment plant for biodegradation, focusing mainly on novel genes and pathways of phenol and aromatic compound degradation. The sequence analysis of selected clones yielded 129,635 reads at an estimated 17-fold coverage. The phylogenetic analysis showed Burkholderiales and Rhodocyclales as the most abundant orders among the selected fosmid clones. The MG-RAST analysis revealed a broad metabolic profile with important functions for wastewater treatment, including metabolism of aromatic compounds, nitrogen, sulphur and phosphorus. The predicted 2,276 proteins included phenol hydroxylases and cathecol 2,3- dioxygenases, involved in the catabolism of aromatic compounds, such as phenol, byphenol, benzoate and phenylpropanoid. The sequencing of one fosmid insert of 33 kb unraveled the gene that permitted the host, Escherichia coli EPI300, to grow in the presence of aromatic compounds. Additionally, the comparison of the whole fosmid sequence against bacterial genomes deposited in GenBank showed that about 90% of sequence showed no identity to known sequences of Proteobacteria deposited in the NCBI database. This study surveyed the functional potential of fosmid clones for aromatic compound degradation and contributed to our knowledge of the biodegradative capacity and pathways of microbial assemblages present in refinery wastewater treatment system.

Changes in the microbial community structure of bacteria, archaea and fungi in response to elevated CO(2) and warming in an Australian native grassland soil.

The microbial community structure of bacteria, archaea and fungi is described in an Australian native grassland soil after more than 5 years exposure to different atmospheric CO2 concentrations ([CO2]) (ambient, +550 ppm) and temperatures (ambient, + 2°C) under different plant functional types (C3 and C4 grasses) and at two soil depths (0-5 cm and 5-10 cm). Archaeal community diversity was influenced by elevated [CO2], while under warming archaeal 16S rRNA gene copy numbers increased for C4 plant Themeda triandra and decreased for the C3 plant community (P < 0.05). Fungal community diversity resulted in three groups based upon elevated [CO2], elevated [CO2] plus warming and ambient [CO2]. Overall bacterial community diversity was influenced primarily by depth. Specific bacterial taxa changed in richness and relative abundance in response to climate change factors when assessed by a high-resolution 16S rRNA microarray (PhyloChip). Operational taxonomic unit signal intensities increased under elevated [CO2] for both Firmicutes and Bacteroidetes, and increased under warming for Actinobacteria and Alphaproteobacteria. For the interaction of elevated [CO2] and warming there were 103 significant operational taxonomic units (P < 0.01) representing 15 phyla and 30 classes. The majority of these operational taxonomic units increased in abundance for elevated [CO2] plus warming plots, while abundance declined in warmed or elevated [CO2] plots. Bacterial abundance (16S rRNA gene copy number) was significantly different for the interaction of elevated [CO2] and depth (P < 0.05) with decreased abundance under elevated [CO2] at 5-10 cm, and for Firmicutes under elevated [CO2] (P < 0.05). Bacteria, archaea and fungi in soil responded differently to elevated [CO2], warming and their interaction. Taxa identified as significantly climate-responsive could show differing trends in the direction of response ('+' or '-') under elevated CO2 or warming, which could then not be used to predict their interactive effects supporting the need to investigate interactive effects for climate change. The approach of focusing on specific taxonomic groups provides greater potential for understanding complex microbial community changes in ecosystems under climate change.

Phylogenetic and functional diversity of metagenomic libraries of phenol degrading sludge from petroleum refinery wastewater treatment system.

In petrochemical refinery wastewater treatment plants (WWTP), different concentrations of pollutant compounds are received daily in the influent stream, including significant amounts of phenolic compounds, creating propitious conditions for the development of particular microorganisms that can rapidly adapt to such environment. In the present work, the microbial sludge from a refinery WWTP was enriched for phenol, cloned into fosmid vectors and pyrosequenced. The fosmid libraries yielded 13,200 clones and a comprehensive bioinformatic analysis of the sequence data set revealed a complex and diverse bacterial community in the phenol degrading sludge. The phylogenetic analyses using MEGAN in combination with RDP classifier showed a massive predominance of Proteobacteria, represented mostly by the genera Diaphorobacter, Pseudomonas, Thauera and Comamonas. The functional classification of phenol degrading sludge sequence data set generated by MG-RAST showed the wide metabolic diversity of the microbial sludge, with a high percentage of genes involved in the aerobic and anaerobic degradation of phenol and derivatives. In addition, genes related to the metabolism of many other organic and xenobiotic compounds, such as toluene, biphenyl, naphthalene and benzoate, were found. Results gathered herein demonstrated that the phenol degrading sludge has complex phylogenetic and functional diversities, showing the potential of such community to degrade several pollutant compounds. This microbiota is likely to represent a rich resource of versatile and unknown enzymes which may be exploited for biotechnological processes such as bioremediation.