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N-dependent dynamics of root growth and nitrate and ammonium uptake are altered by the bacterium Herbaspirillum seropedicae in the cereal model Brachypodium distachyon.

Weiqi KuangStefan SanowJana M KelmMark Müller-LinowPeter AndeerDietrich KohlheyerTrent R NorthenJohn P VogelMichelle WattBorjana Arsova
Published in: Journal of experimental botany (2022)
Nitrogen (N) fixation in cereals by root-associated bacteria is a promising solution for reducing use of chemical N fertilizers in agriculture. However, plant and bacterial responses are unpredictable across environments. We hypothesized that cereal responses to N-fixing bacteria are dynamic, depending on N supply and time. To quantify the dynamics, a gnotobiotic, fabricated ecosystem (EcoFAB) was adapted to analyse N mass balance, to image shoot and root growth, and to measure gene expression of Brachypodium distachyon inoculated with the N-fixing bacterium Herbaspirillum seropedicae. Phenotyping throughput of EcoFAB-N was 25-30 plants h-1 with open software and imaging systems. Herbaspirillum seropedicae inoculation of B. distachyon shifted root and shoot growth, nitrate versus ammonium uptake, and gene expression with time; directions and magnitude depended on N availability. Primary roots were longer and root hairs shorter regardless of N, with stronger changes at low N. At higher N, H. seropedicae provided 11% of the total plant N that came from sources other than the seed or the nutrient solution. The time-resolved phenotypic and molecular data point to distinct modes of action: at 5 mM NH4NO3 the benefit appears through N fixation, while at 0.5 mM NH4NO3 the mechanism appears to be plant physiological, with H. seropedicae promoting uptake of N from the root medium.Future work could fine-tune plant and root-associated microorganisms to growth and nutrient dynamics.
Keyphrases
  • gene expression
  • cell wall
  • minimally invasive
  • dna methylation
  • nitric oxide
  • climate change
  • high resolution
  • high throughput
  • machine learning
  • photodynamic therapy
  • amino acid
  • deep learning
  • data analysis
  • single cell