The connection between the antibiotic resistome and nitrogen-cycling microorganisms in paddy soil is enhanced by application of chemical and plant-derived organic fertilizers.

Environ Res

State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Environment, Resource, Soil and Fertilizers, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China. Electronic address:

Published: February 2024

Antibiotic resistant genes (ARGs) present significant risks to environments and public health. In particular, there is increasing awareness of the role of soil nitrogen in ARG dissemination. Here, we investigated the connections between antibiotic resistome and nitrogen-cycling microbes in paddy soil by performing five-year field experiments with the treatments of no nitrogen fertilization (CK), reduced chemical nitrogen fertilization (LN), conventional chemical nitrogen fertilization (CN) and plant-derived organic nitrogen fertilization (ON). Compared with CK treatment, CN and ON treatments significantly increased soil NH and TN concentrations by 25.4%-56.5% and 10.4%-20.1%, respectively. Redundancy analysis revealed significantly positive correlation of NH with most ARGs, including tetA, macB and barA. Correspondingly, CN and ON treatments enhanced ARG abundances by 21.9%-23.2%. Moreover, CN and ON treatments promoted nitrate/nitrite-reducing bacteria and linked the corresponding N-cycling functional genes (narG, narH, nirK and nrfA) with most ARGs. Metagenomic binning was performed and identified Gemmatimonadaceae, Caulobacteraceae, Ilumatobacteraceae and Anaerolineaceae as hosts for both ARGs and nitrate/nitrite reduction genes that were enriched by CN and ON treatments. Soil resistome risk score analysis indicated that, although there was increased relation of ARG to nitrogen-cycling microorganisms with nitrogen fertilizer application, the environmental risk of ARGs was not increased due to the lower distribution of ARGs in pathogens. This study contributed to a deeper understanding of the role of soil nitrogen in shaping ARG profiles and controlling soil resistome risk.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.envres.2023.117880DOI Listing

Publication Analysis

Top Keywords

nitrogen fertilization
16
antibiotic resistome
8
resistome nitrogen-cycling
8
nitrogen-cycling microorganisms
8
paddy soil
8
plant-derived organic
8
role soil
8
soil nitrogen
8
chemical nitrogen
8
soil resistome
8

Similar Publications

Nitrogen (N) is one of the three major elements required for plant growth and development. It is of great significance to study the effects of different nitrogen application levels on the growth and root exudates of Phlomoides rotata, and can provide a theoretical basis for its scientific application of fertilizer to increase production. In this study, Phlomoides rotata were grown under different nitrogen conditions for two months.

View Article and Find Full Text PDF

Greenhouse gas (GHG) emissions from livestock ruminants, particularly methane (CH), nitrous oxide, and indirectly ammonia (NH) significantly contribute to climate change and global warming. Conventional monoculture swards for cattle feeding, such as perennial ryegrass or Italian ryegrass, usually require substantial fertiliser inputs. Such management elevates soil mineral nitrogen levels, resulting in GHG emissions and potential water contamination.

View Article and Find Full Text PDF

Nitrogen deposition continues to change grassland plant community composition particularly in more mesic systems; however, whether these altered plant communities will respond differently to other global change factors remains to be seen. Here, we explore how nutrient-altered tallgrass prairie responds to drought. Seven years of nutrient treatments (control, nitrogen (N), phosphorus (P), and N + P) resulted in significantly different plant communities.

View Article and Find Full Text PDF

Solar-powered pumping at a remote denitrifying bioreactor.

J Environ Manage

December 2024

Department of Crop Sciences, University of Illinois at Urbana-Champaign, AW-101 Turner Hall, 1103 South Goodwin Avenue, Urbana, IL, USA. Electronic address:

Pumping surface water from a ditch into a denitrifying woodchip bioreactor could improve nitrate-nitrogen (N) removal by minimizing flow variabilities such as early flow cessation at a given subsurface drainage outlet and flashy drainage hydrographs. Few field-scale subsurface drainage bioreactors with pumping configurations have been assessed. Such evaluations would help better bound reasonable expectations of the benefits and drawbacks at these more advanced bioreactors.

View Article and Find Full Text PDF

From Images to Loci: Applying 3D Deep Learning to Enable Multivariate and Multitemporal Digital Phenotyping and Mapping the Genetics Underlying Nitrogen Use Efficiency in Wheat.

Plant Phenomics

December 2024

Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production, Co-sponsored by Province and Ministry, College of Agriculture, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing 210095, China.

The selection and promotion of high-yielding and nitrogen-efficient wheat varieties can reduce nitrogen fertilizer application while ensuring wheat yield and quality and contribute to the sustainable development of agriculture; thus, the mining and localization of nitrogen use efficiency (NUE) genes is particularly important, but the localization of NUE genes requires a large amount of phenotypic data support. In view of this, we propose the use of low-altitude aerial photography to acquire field images at a large scale, generate 3-dimensional (3D) point clouds and multispectral images of wheat plots, propose a wheat 3D plot segmentation dataset, quantify the plot canopy height via combination with PointNet++, and generate 4 nitrogen utilization-related vegetation indices via index calculations. Six height-related and 24 vegetation-index-related dynamic digital phenotypes were extracted from the digital phenotypes collected at different time points and fitted to generate dynamic curves.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!