With the availability of genome-editing technologies and genomic resources (plant and pathogen genome sequences), possibilities of breeding next-generation crops with durable resistance to diseases is bright.  The defense mechanism of plants against the pathogens is a highly complex energy consuming process involving the intruder’s recognition, prevention of its development and counteracting the effects of its products. Plants need to allocate energy for this without perturbance to their normal growth functions. Trade-off between plant’s defense and growth reflecting in yield is encountered as an off-target effect in some experiments of genome editing for disease resistance, as we attempt to gain deeper insights on the plant’s response to resist the pathogen invasion causing disease. Well studied defense-growth trade-off originate from complex crosstalk between defense-related (salicylic acid jasmonic acid and ethylene), and growth-associated (gibberellins, auxin and brassinosteroids) phytohormones, besides that influenced by autoimmunity cell death and accumulation of reactive oxygen species (ROS).

A quantitative review and meta-analysis (in the modern-day terminologies) on the patterns of the cost of resistance (Bergelson and Purrington 1966) concluded that plants intrinsically meet this situation to reduce/avoid the costs by modulating the expression of resistance genes or by expressing them at specific times or in tissues. Further, the cost of resistance in plants varies for the same trait in different genetic backgrounds. This genetic milieu might differ widely with the plant genotypes.

Constitutively activated immunity upon pathogen recognition affect plant growth resulting in low yield. Plants have also evolved mechanisms for maintaining a physiological equilibrium in their response to pathogen attack (immune homeostasis) in order to avoid the potential cost involved in redundant defense reactions through regulation of immune suppressive pathways.

In this context, a significant and compelling recent publication involving a comprehensive long-term investigation by a three-nation scientists team advances our understanding of molecular mechanisms regulating immune homeostasis in plants for balancing the trade-off between disease resistance and yield.

Using rice-Magnaporthe oryzae pathosystem, Gao et al. (2021) portrays immune homeostasis, a conserved metabolic network involving a process of self-regulating physiological host response in rice. This integrates the functioning of a calcium sensor, a susceptibility gene, and the levels of reactive oxygen species (ROS) under control for balancing plant defense and growth fitness. In their exercise, a hitherto unknown phenomenon of both pathogen and plant factors suppressing plant immune responses through a common molecular mechanism has also been revealed.

Early response to pathogen attack is characterized by the generation of ROS including hydrogen peroxide (H₂O₂), a process referred to as the oxidative burst. ROS execute the hypersensitive response limiting the pathogen spread. Elevated levels of ROS accumulating in the plant cells as a result of constitutive mechanism is detrimental to plant growth.  In the presence of a pathogen, suppressing H₂O₂ accumulation leads to tissue susceptibility. The host factor is a C2 domain Ca²⁺ sensor, RESISTANCE OF RICE TO DISEASESES1 (ROD1) that is encoded by the rice susceptibility-like gene ROD1. The susceptibility factor, ROD1 recruits and promotes degradation of H₂O₂ by a catalase, CatB in a Ca⁺-dependent manner. This ROS scavenging activity prevents cell death and allow the infection process to continue unhindered. Abolishing the suppression of H₂O₂ accumulation by disrupting ROD1 functions, provides resistance at the expense of growth. The authors engage mechanistic biochemistry to explain the stability of the protein ROD1 by the process of ubiquitylation with a pair of E3 ubiquitin ligases, RIP1 (ROD1-INTERACTING PROTEIN) and APIP6 (AvrPiz-t INTERACTING PROTEIN) for finetuning the ROS scavenging activity. Knocking out RIP1 and APIP6 stabilises ROD1 and compromises resistance to the pathogens tested, suggesting that these two E3 ubiquitin ligases regulate ROD1 degradation for activating optimal immune responses in rice.

In a similar manner, the blast pathogen secreted effector protein, AvrPiz-t structurally mimics ROD1 and performs identical ROS scavenging to inhibit host immunity for promoting virulence using the same host signalling mechanism. The fungal effector also shares the same ubiquitylation process of protein degradation mechanism of the host for regulating host immunity for its benefit.

Gao et al. (2021) also discovered, a natural ROD1 allele in a rice line from a japonica breeding population grown under blast nursery conditions with heavy disease pressure. The rod1 line was detected by its better growth and yield (more seeds) than the parent japonica rice. ROD1 allele frequency reveals its supspecies-specific occurrence, and its distribution is more prevalent in low-altitude indica rice than in japonica varieties. More importantly, this variant of ROD1 conferring disease resistance does not affect other agronomic traits. This emphasizes its significance in balancing immunity and growth in plants. Further, the rod1mutant exhibits broad-spectrum resistance to important multiple fungal and bacterial rice pathogens, causing blast, sheath blight and bacterial blight, and may be of value for balancing high yield and disease resistance in crop breeding. Moreover, ROD1 orthologs are found across the flowering plants, but not in lower plants. The protein sequences of these orthologs have high sequence similarity in monocot crops, while they are diverged in Brassicaceae (Arabidopsis). CRISPR-CAS-mutated maize line (CR-zmrod1) exhibits resistance to Rhizoctonia solani (sheath blight pathogen) through enhanced expression of pathogenesis-related (PR) gene indicating that ROD1 and its orthologs constitute a distinct type of susceptibility genes with a conserved role across cereals.

Gao et al. (2021) pinpoint two of the perplexing areas for future study in this work. Although the Ca²⁺ sensor ROD1 and the fungal effector AvrPiz-t stimulates the prime step of inducing the catalase CatB for H₂O₂ degradation, functional biochemistry of this is not clear. Despite the fact that the sensor binds and senses calcium, its contribution in regulating calcium signalling in immunity is yet to be revealed.

One third of the known bacterial blight resistance genes are recessive in nature. Of these, only three of the naturally occurring genes (xa5, xa13 and xa25) have been characterized until now.  These genes have originated through mutations in the respective dominant susceptibility alleles like rod1 studied by Gao et al. (2021). This gene has the added advantage of contributing resistance altogether for three (bacterial blight, blast and sheath blight) rice diseases of great significance. While most of the plant disease resistance genes encode nucleotide-binding (NB)-leucine-rich repeat (LRR)-type proteins, the rice bacterial blight resistance genes encode various types of proteins. Thus, the nature of resistance is bound to differ providing opportunities for the detection of novel modes of resistance mechanisms. This might also impede or slow down the usual arms race between the pathogen and the host. Though the past experience show that recessive resistance is sustainable for a longer period, their deployment singly has become vulnerable for pathogen attack with time. However, their use in combination with other resistance genes has proved helpful in increasing resistance substantially.

This study serves as an example of how basic science can open opportunities and provide novel target in crop improvement for broad-spectrum (across multiple pathogens) disease resistance without fitness costs.

References

Bergelson J, Purrington C B. 1996. Surveying patterns in the cost of resistance in plants.
American Naturalist 148, 536-558.

Gao M, He Y. Xin Y. and others. 2021. Ca2+ sensor-mediated ROS scavenging suppresses rice immunity and is exploited by a fungal effector. Cell 184, 5391-5404.