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Review
. 2018 Dec 1;59(12):2398-2408.
doi: 10.1093/pcp/pcy185.

Uncoiling CNLs: Structure/Function Approaches to Understanding CC Domain Function in Plant NLRs

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Free PMC article
Review

Uncoiling CNLs: Structure/Function Approaches to Understanding CC Domain Function in Plant NLRs

Adam R Bentham et al. Plant Cell Physiol. .
Free PMC article

Abstract

Plant nucleotide-binding leucine-rich repeat receptors (NLRs) are intracellular pathogen receptors whose N-terminal domains are integral to signal transduction after perception of a pathogen-derived effector protein. The two major plant NLR classes are defined by the presence of either a Toll/interleukin-1 receptor (TIR) or a coiled-coil (CC) domain at their N-terminus (TNLs and CNLs). Our knowledge of how CC domains function in plant CNLs lags behind that of how TIR domains function in plant TNLs. CNLs are the most abundant class of NLRs in monocotyledonous plants, and further research is required to understand the molecular mechanisms of how these domains contribute to disease resistance in cereal crops. Previous studies of CC domains have revealed functional diversity, making categorization difficult, which in turn makes experimental design for assaying function challenging. In this review, we summarize the current understanding of CC domain function in plant CNLs, highlighting the differences in modes of action and structure. To aid experimental design in exploring CC domain function, we present a 'best-practice' guide to designing constructs through use of sequence and secondary structure comparisons and discuss the relevant assays for investigating CC domain function. Finally, we discuss whether using homology modeling is useful to describe putative CC domain function in CNLs through parallels with the functions of previously characterized helical adaptor proteins.

Figures

Fig. 1
Fig. 1
Comparison of known CC domain functions. (A) Venn diagram of the three major CC domain functions assayed: the ability to induce cell death autonomously (yellow), the ability to self-associate (green) and the ability of the CC domain to interact with a cofactor (blue). The selected CC domains analyzed here have been placed in regions that correlate with observed functions. CC domains from all subclasses can be found across all regions of the Venn diagram, demonstrating little correlation between function and subclass. The one exception to this is Bs2 from the CCCAN subclasses, for which there are no observed functions in any of the three categories and is depicted in an orange circle separated from the other CNLs. (B) A table of reported functions of the CC domains analyzed here, accompanied by the studies in which they were observed. As with (A), little correlation can be seen between CC domain function and subclass assignment, with the exception of CC domains that belong to the monophyletic CCR and I2-like subclasses.
Fig. 2
Fig. 2
Secondary structure alignment of CC domains. The first 220 amino acids of all selected NLRs were subjected to the PSIPRED (Buchan et al. 2013) secondary structure prediction server and sorted by CC domain subclass. The CC domains assigned to the CCEDVID subclass are in the blue box, with the CC domains of the I2-like, CCCAN and CCR in yellow, green and purple boxes, respectively. The predicted α-helices and β-strands of the CC domains are shown as red cylinders and yellow arrows, respectively. The secondary structures of the NB-ARC domain are represented by white shapes with dashed lines. The start of the NB-ARC domains was predicted with Pfam (Finn et al. 2016). Despite all being largely helical, it is clear that the position of the secondary structures in CC domains varies greatly between NLRs.
Fig. 3
Fig. 3
Currently known experimentally determined CC domain structures and their predicted secondary structure. (A) The three-dimensional structures of Sr33, MLA10 and Rx CC domains. The Sr33 and Rx CC domains maintain a monomeric four-helix bundle fold. However, MLA10 CC forms an extended helix–loop–helix structure and is thought to form an obligate dimer. Despite the differences in structures, Sr33 and MLA10 are orthologs (Periyannan et al. 2013). (B) Secondary structure predictions of the Sr33, MLA10 and Rx CC domains. Highlighted on the secondary structures are the regions represented in the crystal structures compared with the regions required for inducing an HR-like phenotype in model plants. The structures of the MLA10 and Sr33 CC domains do not represent functional HR signaling units, which is likely to be compromised by the truncation of the fourth α-helix, as seen in the secondary structure prediction. The Rx CC domain structure comprises an entire four-helix bundle; however, this region does not display autonomous cell death signaling in model plants.
Fig. 4
Fig. 4
Homology modeling of CC domains compared with experimentally determined structural data. Initial homology models were generated for each of the CC domains previously analyzed in Figs. 1 and 2. For each of the CC domains, sequences from the distal N-terminus to the start of the NB-ARC domain (as predicted by Pfam) were used to generate the models. Only two templates were consistently selected for modeling by PHYRE2 (when excluding the MLA10 CC domain crystal structure, PDB: 3QFL). These were the NMR structure of the N-terminal domain of MLKL (PDB: 2MSV) for CC domains of the CCR subclass, and the crystal structure CARD domain of CED-4 (PDB: 2A5Y) for all other CC domains from the CCEDVID, CCCAN, and I2-like subclasses. Models of the ADR1 and Sr33 CC domains were generated by one to one threading as representatives of the CC domain homology models based on the two templates, 2MSV and 2A5Y, using domain boundaries defined by secondary structure and cell death signaling capacity in planta. (A) The homology model of the ADR1 CC domain (right, in violet) is shown as a representative of the CCR subclass. Although only sharing 17% sequence identity to MLKL (structure on the left, shown in blue), the model generated covered 89% of the query sequence, modeling residues 13–146 (133 of 150 residues input) with 99.5% confidence. (B) The homology model of the Sr33 CC domain (right, shown in cyan), chosen as the representative of the CCEDVID, CCCAN and I2-like subclasses. The Sr33 CC domain shares 10% sequence identity with the CED-4 CARD (structure on the left, shown in green), and the homology model generated covers 61% of the query sequence modeling residues 44–132 (88 of 144 residues input) with a confidence of 95.5%. (C) Left: superimposition of the CC domain homology model of ADR1 (violet) with the NMR structure of the Sr33 CC domain (red) using combinatorial extension. Of the 133 residues modeled, 96 residues of the ADR1 homology model could be superimposed on the Sr33 CC domain NMR structure with a root mean square deviation of 3.88 �. This shows similarity in the overall fold, and suggests that the ADR1 CC homology model may represent a reasonable structure for this CC domain. Right: superimposition of the Sr33 CC domain homology model (cyan) with the NMR structure of the Sr33 CC domain (red) using combinatorial extension. The Sr33 homology model does not represent an accurate depiction of the Sr33 CC domain as seen by the poor superimposition on the Sr33 NMR structure with 56 of the 88 modeled residues superimposed with a root mean square deviation of 6.04 �. This is despite the high confidence score assigned by PHYRE2 to the model.

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