Genome-Scale Metabolic Modelling of Lifestyle Changes in Rhizobium leguminosarum

Schulte, Carolin C. M.; Ramachandran, Vinoy K.; Papachristodoulou, Antonis; Poole, Philip S.

doi:10.1128/msystems.00975-21

Cited by 10 publications

(6 citation statements)

References 101 publications

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“…Sequencing was carried out by Novogene using the Illumina NovoSeq 6000. Analysis was performed as described previously [41]. Data has been uploaded to the NCBI SRA database with the accession number PRJNA811156.…”

Section: Methodsmentioning

confidence: 99%

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Factors governing attachment ofRhizobium leguminosarumto legume roots

Parsons

Cocker

East

et al. 2022

Preprint

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Primary attachment of rhizobia to host legume roots depends on pH and is the first physical interaction during nodulation. Genome-wide insertion sequencing, luminescence-based attachment assays and proteomic analysis demonstrate primary attachment of Rhizobium leguminosarum biovar viciae 3841 to Pisum sativum (pea) roots is more complex than previously thought. In total, 115 proteins are needed for initial attachment under one or more test conditions (acid, neutral or alkaline pH), with 22 required under all conditions. These include cell-surface filamentous hemagglutinin adhesin (RL4382) and its transporter (RL4381), transmembrane protein RL2400, RL3752 (PssA, glycosyl transferase) affecting capsular polysaccharide and transcriptional regulator RL4145 (PckR). RNASeq was used to determine targets of RL4145 (PckR) and regulator RL3453. The 54 proteins required for attachment at pH 7.0 were investigated for nodulation phenotypes. Glucomannan biosynthesis protein A (GmsA) is needed at pH 6.5 and pH 7.0. Membrane proteins DgkA and ImpA are required specifically at pH 6.5, and RpoZ at pH 7.5. Sonicated cell surface fractions inhibited root attachment at alkaline pH but no overlap between proteins identified by proteomic and INseq analysis, suggests there is no single rhicadhesin needed for alkaline attachment. Our results demonstrate the complexity of primary root attachment and diversity of mechanisms involved.

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Section: Methodsmentioning

confidence: 99%

“…Analysis was performed as described previously [41]. Data has been uploaded to the NCBI SRA database with the accession number PRJNA811156.…”

Section: Rnaseqmentioning

confidence: 99%

Factors governing attachment ofRhizobium leguminosarumto legume roots

Parsons

Cocker

East

et al. 2022

Preprint

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“…Consequently, we need to develop model systems, such as novel in vitro experimental setups and data interpretative models, to predict the outcomes from lab-scale analyses and trials to open field applications [ 150 ]. Systems biology approaches have proved to be powerful in finding key parameters in complex biological phenomena and have already shown their ability in modeling rhizobia symbiotic interaction [ 37 , 151 , 152 ]. Ecological modeling of plant–rhizobium–soil biota interactions [ 153 ], coupled with molecular data coming from genome analyses (see, for instance, [ 154 ] concerning human–microbe interaction), should be prioritized in order to find predictors (especially in the rhizobia genomes) of the goodness of the symbiotic phenotype in nature (and field conditions).…”

Section: Future Directionsmentioning

confidence: 99%

Scent of a Symbiont: The Personalized Genetic Relationships of Rhizobium—Plant Interaction

Cangioli

Vaccaro

Fini

et al. 2022

IJMS

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Many molecular signals are exchanged between rhizobia and host legume plants, some of which are crucial for symbiosis to take place, while others are modifiers of the interaction, which have great importance in the competition with the soil microbiota and in the genotype-specific perception of host plants. Here, we review recent findings on strain-specific and host genotype-specific interactions between rhizobia and legumes, discussing the molecular actors (genes, gene products and metabolites) which play a role in the establishment of symbiosis, and highlighting the need for research including the other components of the soil (micro)biota, which could be crucial in developing rational-based strategies for bioinoculants and synthetic communities’ assemblage.

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“…This provides a global view of the metabolism of an organism under steady‐state conditions without specific information on the kinetic parameters of each enzyme. FBA model reconstructions have been built for several N‐fixing legume symbionts, including Sinorhizobium fredii (Contador et al ., 2020), Bradyrhizobium diazoefficiens (Yang et al ., 2017), Rhizobium etli (Resendis‐Antonio et al ., 2007), Rhizobium leguminosarum (Schulte et al ., 2021, 2022), and Sinorhizobium meliloti (Zhao et al ., 2012; diCenzo et al ., 2016, 2018, 2020). Most studies investigate symbiotic N fixation by performing simulations with isolated bacteroids, investigating individual processes that would typically be controlled by the plant.…”

Section: Introductionmentioning

confidence: 99%

A genome‐scale metabolic reconstruction of soybean and Bradyrhizobium diazoefficiens reveals the cost–benefit of nitrogen fixation

Holland,

Matthews,

Bota

et al. 2023

New Phytologist

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Summary Nitrogen‐fixing symbioses allow legumes to thrive in nitrogen‐poor soils at the cost of diverting some photoassimilate to their microsymbionts. Effort is being made to bioengineer nitrogen fixation into nonleguminous crops. This requires a quantitative understanding of its energetic costs and the links between metabolic variations and symbiotic efficiency. A whole‐plant metabolic model for soybean (Glycine max) with its associated microsymbiont Bradyrhizobium diazoefficiens was developed and applied to predict the cost–benefit of nitrogen fixation with varying soil nitrogen availability. The model predicted a nitrogen‐fixation cost of c. 4.13 g C g−1 N, which when implemented into a crop scale model, translated to a grain yield reduction of 27% compared with a non‐nodulating plant receiving its nitrogen from the soil. Considering the lower nitrogen content of cereals, the yield cost to a hypothetical N‐fixing cereal is predicted to be less than half that of soybean. Soybean growth was predicted to be c. 5% greater when the nodule nitrogen export products were amides versus ureides. This is the first metabolic reconstruction in a tropical crop species that simulates the entire plant and nodule metabolism. Going forward, this model will serve as a tool to investigate carbon use efficiency and key mechanisms within N‐fixing symbiosis in a tropical species forming determinate nodules.

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Genome-Scale Metabolic Modelling of Lifestyle Changes in Rhizobium leguminosarum

Abstract: Rhizobia are soil bacteria that induce nodule formation on plant roots and differentiate into nitrogen-fixing bacteroids. A detailed understanding of this complex symbiosis is essential for advancing ongoing efforts to engineer novel symbioses with cereal crops for sustainable agriculture.

Cited by 10 publications

References 101 publications

Factors governing attachment ofRhizobium leguminosarumto legume roots

Factors governing attachment ofRhizobium leguminosarumto legume roots

Scent of a Symbiont: The Personalized Genetic Relationships of Rhizobium—Plant Interaction

A genome‐scale metabolic reconstruction of soybean and Bradyrhizobium diazoefficiens reveals the cost–benefit of nitrogen fixation

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