CaProDH2-mediated modulation of proline metabolism confers tolerance to Ascochyta in chickpea under drought
Patil, M.; Pandey, P.; Irrulappan, V.; Singh, A.; Verma, P.; Ranjan, A.; Senthil-Kumar, M.
Show abstract
Drought and leaf blight caused by the fungus Ascochyta rabiei often co-occur in chickpea (Cicer arietinum)-producing areas. While the responses of chickpea to either drought or A. rabiei infection have been extensively studied, their combined effect on plant defense mechanisms is unknown. Fine modulation of stress-induced signaling pathways under combined stress is an important stress adaptation mechanism that warrants a better understanding. Here we show that drought facilitates resistance against A. rabiei infection in chickpea. The analysis of proline levels and gene expression profiling of its biosynthetic pathway under combined drought and A. rabiei infection revealed the gene encoding proline dehydrogenase (CaProDH2) as a strong candidate conferring resistance to A. rabiei infection. Transcript levels of CaProDH2, pyrroline-5-carboxylate (P5C) quantification, and measurement of mitochondrial reactive oxygen species (ROS) production showed that fine modulation of the proline-P5C cycle determines the observed resistance. In addition, CaProDH2-silenced plants lost basal resistance to A. rabiei infection induced by drought, while overexpression of the gene conferred higher resistance to the fungus. We suggest that the drought-induced accumulation of proline in the cytosol helps maintain cell turgor and raises mitochondrial P5C contents by a CaProDH2-mediated step, which results in ROS production that boosts plant defense responses and confers resistance to A. rabiei infection. Our findings indicate that manipulating the proline-P5C pathway may be a possible strategy for improving stress tolerance in plants suffering from combined drought and A. rabiei infection.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The Arabidopsis leucine-rich repeat receptor kinase MIK2 is a crucial component of pattern-triggered immunity responses to Fusarium fungi 95%
- Overexpression of NDR1 Leads to Pathogen Resistance at Elevated Temperatures 95%
- A plastidial retrograde-signal potentiates biosynthesis of systemic stress response activators 95%
Similar papers in this journal
- Estradiol-inducible AvrRps4 expression reveals distinct properties of TIR-NLR-mediated effector-triggered immunity 96%
- Barley shows reduced Fusarium Head Blight under drought and modular expression of differential expressed genes under combined stress 96%
- Early root-root interactions weaken foliar defense responses against Septoria tritici blotch in a durum wheat varietal mixture 96%
Similar papers in this journal
- Identification of candidate susceptibility genes to Puccinia graminis f. sp. tritici in wheat 96%
- Expression of a fungal lectin in Arabidopsis enhances plant growth and resistance towards microbial pathogens and plant-parasitic nematode 96%
- AP2/ERF transcription factor NbERF-IX-33 is involved in the regulation of phytoalexin production for the resistance of Nicotiana benthamiana to Phytophthora infestans. 96%
Similar papers in this journal
- Chitosan primes plant defence mechanisms against Botrytis cinerea, including expression of Avr9/Cf-9 rapidly-elicited genes 96%
- De novo indol-3-ylmethyl glucosinolate biosynthesis, and not long-distance transport, contributes to defence of Arabidopsis against powdery mildew 96%
- Constitutive expression of JASMONATE RESISTANT 1 elevates content of several jasmonates and primes Arabidopsis thaliana to better withstand drought 96%
Similar papers in this journal
- Phosphate-induced resistance to pathogen infection in Arabidopsis 97%
- Spatial accumulation of salicylic acid is regulated by RBOHD in potato immunity against viruses 95%
- Identification of INOSITOL PHOSPHORYLCERAMIDE SYNTHASE 2 (IPCS2) as a new rate-limiting component in Arabidopsis pathogen entry control 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.