Contribution of pathogenic fungi to N2O emissions increases temporally in intensively managed strawberry cropping soil.

Intensively managed agriculture land is a significant contributor to nitrous oxide (N2O) emissions, which adds to global warming and the depletion of the ozone layer. Recent studies have suggested that fungal dominant N2O production may be promoted by pathogenic fungi under high nitrogen fertilization and continuous cropping. Here, we measured the contribution of fungal communities to N2O production under intensively managed strawberry fields of three continuous cropping years (1, 5, and 10 years) and compared this adjacent bare soil. Higher N2O emission was observed from the 10-year field, of which fungi and prokaryotes accounted for 79.7% and 21.3%, respectively. Fungal population density in the 10-year field soil (4.25 × 105 colony forming units per g (CFU/g) of air-dried soil) was greater than the other cropping years. Illumina MiSeq sequencing of the nirK gene showed that long-term continuous cropping decreased the diversity of the fungal denitrifier community, but increased the abundance of Fusarium oxysporum. Additionally, F. oxysporum produced large amounts of N2O in culture and in sterile 10-year field soil. A systemic infection displayed by bioassay strawberry plants after inoculation demonstrated that F. oxysporum was a pathogenic fungus. Together, results suggest that long-term intensively managed monocropping significantly influenced the denitrifying fungal community and increased their biomass, which increased fungal contribution to N2O emissions and specifically by pathogenic fungi. KEY POINTS: • Distinguishing the role of fungi in long-term continuous cropping field. • Identifying the abundant fungal species with denitrifying ability.

Biochar mitigates the N2O emissions from acidic soil by increasing the nosZ and nirK gene abundance and soil pH.

Nitrous oxide (N2O) is a pervasive greenhouse gas, and soil management practices greatly affect its release into the atmosphere. Soil pH management (particularly increasing the pH) using biochar can seriously affect soil N2O emissions. The current incubation experiment was conducted to explore the response of N2O emissions from acidic soils using various doses of biochar. Soil with a pH of 5.48 was treated with rice straw biochar at different doses (0%, 1% and 2%) and incubated with 60% water-filled pore spaces (WFPS). The experiment was conducted in a completely randomized design (CRD) with three replications. The soil N2O emissions, pH, NH4+-N, NO3--N, microbial biomass carbon (MBC), and nosZ and nirK gene abundance were determined at various intervals throughout the study. The biochar application (2%) increased the soil pH (from 5.48 to 6.11), triggered the transformation of nitrogen, and augmented the abundance of nosZ and nirK genes. Higher magnitudes of cumulative soil N2O emissions (48.60 µg kg-1) were noted in the control (no biochar) compared to 1% (28.10 µg kg-1) and 2% (14.50 µg kg-1) biochar application. The 2% biochar application more effectively decreased the soil N2O emissions, mainly because of the increased nosZ and nirK gene abundance at higher soil pH levels. The findings suggest that the amelioration of acidic soil with rice straw biochar can considerably control soil N2O emissions by elevating the soil pH and the abundance of nosZ and nirK genes.

Characterization of the denitrifying bacterial community in a full-scale rockwool biofilter for compost waste-gas treatment.

The potential denitrification activity and the composition of the denitrifying bacterial community in a full-scale rockwool biofilter used for treating livestock manure composting emissions were analyzed. Packing material sampled from the rockwool biofilter was anoxically batch-incubated with 15N-labeled nitrate in the presence of different electron donors (compost extract, ammonium, hydrogen sulfide, propionate, and acetate), and responses were compared with those of activated sludge from a livestock wastewater treatment facility. Overnight batch-incubation showed that potential denitrification activity for the rockwool samples was higher with added compost extract than with other potential electron donors. The number of 16S rRNA and nosZ genes in the rockwool samples were in the range of 1.64-3.27 × 109 and 0.28-2.27 × 108 copies/g dry, respectively. Denaturing gradient gel electrophoresis analysis targeting nirK, nirS, and nosZ genes indicated that the distribution of nir genes was spread in a vertical direction and the distribution of nosZ genes was spread horizontally within the biofilter. The corresponding denitrifying enzymes were mainly related to those from Phyllobacteriaceae, Bradyrhizobiaceae, and Alcaligenaceae bacteria and to environmental clones retrieved from agricultural soil, activated sludge, freshwater environments, and guts of earthworms or other invertebrates. A nosZ gene fragment having 99% nucleotide sequence identity with that of Oligotropha carboxidovorans was also detected. Some nirK fragments were related to NirK from micro-aerobic environments. Thus, denitrification in this full-scale rockwool biofilter might be achieved by a consortium of denitrifying bacteria adapted to the intensely aerated ecosystem and utilizing mainly organic matter supplied by the livestock manure composting waste-gas stream.

Spatial pattern of functional genes abundance reveals the importance of PhoD gene harboring bacterial community for maintaining plant growth in the tropical forest of Southwestern China.

The concept of microbial functional genes has added a new dimension to microbial ecology research by improving the model of microbial community-ecosystem functions relationship. However, our knowledge vis-à-vis fine-scale spatial distribution pattern of functional genes and their probable impact on plant community in the hyper-diverse tropical forest ecosystem is very limited. Here, we investigated the spatial pattern of functional genes abundance (NirK, AOA, AOB, and PhoD), identified key influencing factors, and distinguished the key functional group supporting the plant community in a tropical rainforest located in Xishuangbanna. In total, 200 soil samples and vegetation data of ~4800 individuals of plants across a 1 ha study area were collected. Our results detected higher spatial variability with a maximum magnitude of abundance for PhoD gene (4.53 × 107 copies) followed by NirK (2.71 × 106 copies), AOA (1.97 × 106 copies), and AOB (7.38 × 104 copies). A strong spatial dependence was observed for PhoD and NirK over the distance of 17 and 18 m, respectively. Interestingly, the N:P stoichiometry played a critical role in structuring the spatial pattern of the most abundant PhoD gene. The significant positive and negative relationship of PhoD with N:P ratio and available phosphorus, respectively, indicated that the P-limiting environment was a driving factor for recruitment of PhoD gene community. The structural equation modeling ascertained the direct positive impact of PhoD on plant biomass and high demand of available P by plants suggesting that the organic phosphorus mineralization process is essential to maintain plant productivity by re-establishing the availability of the most limiting P nutrient. Our preliminary study improves our understanding of how microbial functional genes-environment associations could be used for monitoring soil health and its overall impact on ecosystem multifunctionality. Finally, we intend to conduct the study at a large spatial scale for achieving a holistic view.

Climate and soil parameters are more important than denitrifier abundances in controlling potential denitrification rates in Chinese grassland soils.

Denitrification is an important process that influences nitrogen (N) loss and the production of greenhouse gas in grassland soils. However, the relative contributions of abiotic and biotic factors to soil denitrification potential at the regional and sub-regional scales in grassland ecosystems remain elusive. In this study, soil samples were collected from 21 sites at three steppes of China, including the Inner Mongolia Plateau (IMP), the Xinjiang Autonomous Region (XAR) and the Tibetan Plateau (TP) grasslands. Results showed that the key factors controlling the denitrification potential were regional and scale-dependent. At the sub-regional scales, soil pH, aridity index (AI) and total organic carbon (TOC) explained the highest variances on denitrification potential in the IMP, XAR and TP steppe, respectively. At the regional scale, the mean annual precipitation (MAP) was the most important environmental driver for the denitrification potential. Partial least squares (PLS) path modeling revealed that the MAP might regulate denitrification potential directly and indirectly by its effects on the plant and soil properties. Overall, these results help to improve our understandings on the prediction of the denitrification potential under global changes and revealed that the denitrification potential at various scales could be regulated by the multiple interactions of abiotic and biotic factors.

Comparative analysis of amino acid composition in the active site of nirk gene encoding copper-containing nitrite reductase (CuNiR) in bacterial spp.

The nirk gene encoding the copper-containing nitrite reductase (CuNiR), a key catalytic enzyme in the environmental denitrification process that helps to produce nitric oxide from nitrite. The molecular mechanism of denitrification process is definitely complex and in this case a theoretical investigation has been conducted to know the sequence information and amino acid composition of the active site of CuNiR enzyme using various Bioinformatics tools. 10 Fasta formatted sequences were retrieved from the NCBI database and the domain and disordered regions identification and phylogenetic analyses were done on these sequences. The comparative modeling of protein was performed through Modeller 9v14 program and visualized by PyMOL tools. Validated protein models were deposited in the Protein Model Database (PMDB) (PMDB id: PM0080150 to PM0080159). Active sites of nirk encoding CuNiR enzyme were identified by Castp server. The PROCHECK showed significant scores for four protein models in the most favored regions of the Ramachandran plot. Active sites and cavities prediction exhibited that the amino acid, namely Glycine, Alanine, Histidine, Aspartic acid, Glutamic acid, Threonine, and Glutamine were common in four predicted protein models. The present in silico study anticipates that active site analyses result will pave the way for further research on the complex denitrification mechanism of the selected species in the experimental laboratory.