Computational prediction method to decipher receptor–glycoligand interactions in plant immunity. (19th February 2021)
- Record Type:
- Journal Article
- Title:
- Computational prediction method to decipher receptor–glycoligand interactions in plant immunity. (19th February 2021)
- Main Title:
- Computational prediction method to decipher receptor–glycoligand interactions in plant immunity
- Authors:
- del Hierro, Irene
Mélida, Hugo
Broyart, Caroline
Santiago, Julia
Molina, Antonio - Abstract:
- SUMMARY: Microbial and plant cell walls have been selected by the plant immune system as a source of microbe‐ and plant damage‐associated molecular patterns (MAMPs/DAMPs) that are perceived by extracellular ectodomains (ECDs) of plant pattern recognition receptors (PRRs) triggering immune responses. From the vast number of ligands that PRRs can bind, those composed of carbohydrate moieties are poorly studied, and only a handful of PRR/glycan pairs have been determined. Here we present a computational screening method, based on the first step of molecular dynamics simulation, that is able to predict putative ECD‐PRR/glycan interactions. This method has been developed and optimized with Arabidopsis LysM‐PRR members CERK1 and LYK4, which are involved in the perception of fungal MAMPs, chitohexaose (1, 4‐β‐d ‐(GlcNAc)6 ) and laminarihexaose (1, 3‐β‐d ‐(Glc)6 ). Our in silico results predicted CERK1 interactions with 1, 4‐β‐d ‐(GlcNAc)6 whilst discarding its direct binding by LYK4. In contrast, no direct interaction between CERK1/laminarihexaose was predicted by the model despite CERK1 being required for laminarihexaose immune activation, suggesting that CERK1 may act as a co‐receptor for its recognition. These in silico results were validated by isothermal titration calorimetry binding assays between these MAMPs and recombinant ECDs‐LysM‐PRRs. The robustness of the developed computational screening method was further validated by predicting that CERK1 does not bind the DAMP 1,SUMMARY: Microbial and plant cell walls have been selected by the plant immune system as a source of microbe‐ and plant damage‐associated molecular patterns (MAMPs/DAMPs) that are perceived by extracellular ectodomains (ECDs) of plant pattern recognition receptors (PRRs) triggering immune responses. From the vast number of ligands that PRRs can bind, those composed of carbohydrate moieties are poorly studied, and only a handful of PRR/glycan pairs have been determined. Here we present a computational screening method, based on the first step of molecular dynamics simulation, that is able to predict putative ECD‐PRR/glycan interactions. This method has been developed and optimized with Arabidopsis LysM‐PRR members CERK1 and LYK4, which are involved in the perception of fungal MAMPs, chitohexaose (1, 4‐β‐d ‐(GlcNAc)6 ) and laminarihexaose (1, 3‐β‐d ‐(Glc)6 ). Our in silico results predicted CERK1 interactions with 1, 4‐β‐d ‐(GlcNAc)6 whilst discarding its direct binding by LYK4. In contrast, no direct interaction between CERK1/laminarihexaose was predicted by the model despite CERK1 being required for laminarihexaose immune activation, suggesting that CERK1 may act as a co‐receptor for its recognition. These in silico results were validated by isothermal titration calorimetry binding assays between these MAMPs and recombinant ECDs‐LysM‐PRRs. The robustness of the developed computational screening method was further validated by predicting that CERK1 does not bind the DAMP 1, 4‐β‐d ‐(Glc)6 (cellohexaose), and then probing that immune responses triggered by this DAMP were not impaired in the Arabidopsis cerk1 mutant. The computational predictive glycan/PRR binding method developed here might accelerate the discovery of protein–glycan interactions and provide information on immune responses activated by glycoligands. Significance Statement: Glycans from microbial/plant cell walls have been selected as molecular patterns that are perceived by extracellular ectodomains (ECDs) of plant pattern recognition receptors (PRRs) triggering immune responses. Only a handful of PRR/glycan pairs have been determined. Here we present a computational screening method, based on the first step of molecular dynamics simulation, that predicts putative ECD‐PRR/glycan interactions. This method might accelerate the discovery of protein–glycan interactions and provide information on immune responses activated by novel glycoligands. … (more)
- Is Part Of:
- Plant journal. Volume 105:Number 6(2021)
- Journal:
- Plant journal
- Issue:
- Volume 105:Number 6(2021)
- Issue Display:
- Volume 105, Issue 6 (2021)
- Year:
- 2021
- Volume:
- 105
- Issue:
- 6
- Issue Sort Value:
- 2021-0105-0006-0000
- Page Start:
- 1710
- Page End:
- 1726
- Publication Date:
- 2021-02-19
- Subjects:
- Arabidopsis thaliana -- glycan -- immunity -- isothermal titration calorimetry -- LysM domain -- molecular dynamics -- pattern recognition receptor -- technical advance
Plant molecular biology -- Periodicals
Plant cells and tissues -- Periodicals
Botany -- Periodicals
580 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-313X ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/tpj.15133 ↗
- Languages:
- English
- ISSNs:
- 0960-7412
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6519.200000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16197.xml