Cargando…
Temporal assessment of N-cycle microbial functions in a tropical agricultural soil using gene co-occurrence networks
Microbial nitrogen (N) cycling pathways are largely responsible for producing forms of N that are available for plant uptake or lost from the system as gas or leachate. The temporal dynamics of microbial N pathways in tropical agroecosystems are not well defined, even though they are critical to und...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9928094/ https://www.ncbi.nlm.nih.gov/pubmed/36787300 http://dx.doi.org/10.1371/journal.pone.0281442 |
Sumario: | Microbial nitrogen (N) cycling pathways are largely responsible for producing forms of N that are available for plant uptake or lost from the system as gas or leachate. The temporal dynamics of microbial N pathways in tropical agroecosystems are not well defined, even though they are critical to understanding the potential impact of soil conservation strategies. We aimed to 1) characterize temporal changes in functional gene associations across a seasonal gradient, 2) identify keystone genes that play a central role in connecting N cycle functions, and 3) detect gene co-occurrences that remained stable over time. Soil samples (n = 335) were collected from two replicated field trials in Rwanda between September 2020 and March 2021. We found high variability among N-cycle gene relationships and network properties that was driven more by sampling timepoint than by location. Two nitrification gene targets, hydroxylamine oxidoreductase and nitrite oxidoreductase, co-occurred across all timepoints, indicating that they may be ideal year-round targets to limit nitrification in rainfed agricultural soils. We also found that gene keystoneness varied across time, suggesting that management practices to enhance N-cycle functions such as the application of nitrification inhibitors could be adapted to seasonal conditions. Our results mark an important first step in employing gene networks to infer function in soil biogeochemical cycles, using a tropical seasonal gradient as a model system. |
---|