Bacterial community shifts occur primarily through rhizosphere expansion in response to subsoil amendments.

To comprehensively evaluate the impact of agricultural management practices on soil productivity, it is imperative to conduct a thorough analysis of soil bacterial ecology. Deep-banding nutrient-rich amendments is a soil management practice that aims to improve plant growth and soil structure by addressing the plant-growth constraints posed by dense-clay subsoils. However, the response of bacterial communities to deep-banded amendments has not been thoroughly studied. To address this knowledge gap, we conducted a controlled-environment column experiment to examine the effects of different types of soil amendments (poultry litter, wheat straw + chemical fertiliser and chemical fertiliser alone) on bacterial taxonomic composition in simulated dense-clay subsoils. We evaluated the bacterial taxonomic and ecological group composition in soils beside and below the amendment using 16S rRNA amplicon sequencing and robust statistical methods. Our results indicate that deep-banded amendments alter bacterial communities through direct and indirect mechanisms. All amendments directly facilitated a shift in bacterial communities in the absence of growing wheat. However, a combination of amendments with growing wheat led to a more pronounced bacterial community shift which was distinct from and eclipsed the direct impact of the amendments and plants alone. This indirect mechanism was evidenced to be mediated primarily by plant growth and hypothesised to result from an enhancement in wheat root distribution, density and rhizodeposition changes. Therefore, we propose that subsoil amendments regardless of type facilitated an expansion in the rhizosphere which engineered a substantial plant-mediated bacterial community response within the simulated dense-clay subsoils. Overall, our findings highlight the importance of considering the complex and synergistic interactions between soil physicochemical properties, plant growth and bacterial communities when assessing agricultural management strategies for improving soil and plant productivity.

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.

Biochar reduced extractable dieldrin concentrations and promoted oligotrophic growth including microbial degraders of chlorinated pollutants.

The role of organic amendments for natural degradation of aged persistent organic pollutants (POPs) in agricultural soils remains controversial. We hypothesised that organic amendments enhance bacterial activity and function at the community level, facilitating the degradation of aged POPs. An incubation study was conducted in a closed chamber over 12 months to assess the effects of selected organic amendments on extractable residues of aged dieldrin. The role of bacterial diversity and changes in community function was explored through sequenced marker genes. Linear mixed effect models indicated that, independent of amendment type, cumulative CO2 release was negatively associated with decreases in dieldrin concentration, by up to 7% per µmol CO2-C respired by microorganisms. The addition of poultry litter led to the highest daily carbon mineralisation, which was associated with low dieldrin dissipation after 9 months. In comparison, biochar resulted in significant decreases in extractable dieldrin residues over time, which coincided with shifts towards aerobic, oligotrophic, gram-negative bacteria, some with dehalogenation metabolism, and with increased potentials for biosynthesis of membrane components such as fatty acids and high redox quinones. The results supported an alternative theory that labile carbon promoted blooms of copiotrophic growth, which suppressed the required community-level traits and oligotrophic diversity to degrade chlorinated pollutants.

Highly decomposed organic carbon mediates the assembly of soil communities with traits for the biodegradation of chlorinated pollutants.

To improve biodegradation strategies for chlorinated pollutants, the roles of soil organic matter and microbial function need to be clarified. It was hypothesised that microbial degradation of specific organic fractions in soils enhance community metabolic capability to degrade chlorinated pollutants. This field study used historic records of dieldrin concentrations since 1988 and established relationships between dieldrin dissipation and soil carbon fractions together with bacterial and fungal diversity in surface soils of Kurosol and Chromosol. Sparse partial least squares analysis linked dieldrin dissipation to metabolic activities associated with the highly decomposed carbon fraction. Dieldrin dissipation, after three decades of natural attenuation, was associated with increased bacterial species fitness for the decomposition of recalcitrant carbon substrates including synthetic chlorinated pollutants. These metabolic capabilities were linked to the decomposed carbon fraction, an important driver for the microbial community and function. Common bacterial traits among taxonomic groups enriched in samples with high dieldrin dissipation included their slow growth, large genome and complex metabolism which supported the notion that metabolic strategies for dieldrin degradation evolved in an energy-low soil environment. The findings provide new perspectives for bioremediation strategies and suggest that soil management should aim at stimulating metabolism at the decomposed, fine carbon fraction.

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.

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.

Best practice data life cycle approaches for the life sciences.

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

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.

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.

Microsatellite and Minisatellite Analysis of Leptosphaeria maculans in Australia Reveals Regional Genetic Differentiation.

ABSTRACT The population genetic structure of the fungal pathogen Leptosphaeria maculans was determined in Australia using six microsatellite and two minisatellite markers. Ascospores were sampled from Brassica napus stubble in disease nurseries and commercial fields in different sites over 2 years. The 13 subpopulations of L. maculans exhibited high gene (H = 0.393 to 0.563) and genotypic diversity, with 357 haplotypes identified among 513 isolates. Although the majority of genetic variation was distributed within subpopulations (85%), 10% occurred between the regions of eastern and Western Australia, and 5% within regions. F(ST) analysis of subpopulation pairs also showed the east-west genetic differentiation, whereas factorial correspondence analysis separated Western Australian subpopulations from eastern ones. Bayesian model-based population structure analyses of multilocus haplotypes inferred three distinct populations, one in Western Australia and an admixture of two in eastern Australia. These two regions are separated by 1,200 km of arid desert that may act as a natural barrier to gene flow, resulting in differentiation by random genetic drift. The genetic differentiation of L. maculans isolates between eastern and Western Australia means that these regions can be treated as different management units, and reinforces the need for widespread disease nurseries in each region to screen breeding lines against a range of genetic and pathogenic populations of L. maculans.

Genetic structure of a population of the fungus Leptosphaeria maculans in a disease nursery of Brassica napus in Australia.

Microsatellite, minisatellite and mating type markers were used to determine the genetic structure of the fungus Leptosphaeria maculans within a disease nursery, where Brassica napus lines were screened for resistance to blackleg disease under high inoculum pressure. Fungal isolates were collected from pseudothecia in infected stubble and pycnidia within cotyledon lesions on seedlings within the nursery. Genetic diversity was high with gene diversity at H=0.700 across four polymorphic loci, and genotypic diversity at D=0.993. Among the 159 isolates analysed, 102 multilocus genotypes were identified. The even distribution of mating type idiomorphs MAT1-1 and MAT1-2 and gametic equilibrium within the population provided further evidence of random mating. Genetic diversity was distributed on a very fine scale in the disease nursery. The majority of genetic diversity (67%) was distributed among conidia within a lesion or among ascospores from a piece of stubble, while the remainder (33%) was distributed within lesions on seedlings or different stubble pieces. There were no among-group differences between samples from stubble and seedlings. This is consistent with the low level of genetic differentiation between the ascospore and conidia samples (F (ST)=0.017) indicating that all isolates of L. maculans from the disease nursery most likely belong to one population, and that ascospores form the primary inoculum in the disease nursery.