Temporal assessment of N-cycle microbial functions in a tropical agricultural soil using gene co-occurrence networks

Marie Schaedel, Satoshi Ishii, Hao Wang, Rodney Venterea, Birthe Paul, Mupenzi Mutimura, Julie Grossman

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article numbere0281442
JournalPloS one
Volume18
Issue number2 February
DOIs
StatePublished - Feb 2023

Bibliographical note

Funding Information:
This work was undertaken as part of the CGIAR Research Program (CRP) on Livestock. In addition, it was supported by the OneCGIAR Initiatives on Livestock, Climate and System Resilience (LCSR). We thank all donors that globally support our work through their contributions to the CGIAR system. (Recipient: International Center for Tropical Agriculture) This work was also supported by the National Science Foundation, Graduate Research Fellowship (no. 00074041) and the Doctoral Dissertation Fellowship (University of Minnesota). (Ms. Marie Schaedel). We would like to thank the Rwandan Agricultural Board and Paulin Mutanguha for their support in maintaining field trials. We would also like to thank Solomon Mwendia and An Notenbaert from the International Center for Tropical Agriculture (CIAT) for providing guidance and logistical support. Bonsa Mohamed and Scott Mitchell at the University of Minnesota helped with sample processing and provided technical support.

Publisher Copyright:
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, Non-U.S. Gov't

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