Pseudomonas stutzeri AK17 Mediated Modulation of Plant Defence Responses under Drought Stress

View Dataset
Ritika Jain

Description

Drought is one of the severe abiotic stresses that limits the growth and yield of crops, mainly in arid and semi-arid regions. Cluster bean (Cyamopsis tetragonoloba L.) is relatively tolerant but suffers physiological and biochemical detriments during prolonged water scarcity.  Plant growth-promoting rhizobacteria provide a sustainable biological strategy for improving plant resilience under drought stress. This study demonstrates the potential of P. stutzeri AK17 in mitigating drought stress, which is currently underexplored. Greenhouse experiments were conducted to study the effect of drought on treated and untreated plants by withholding water for 4, 8 and 12 days. Various parameters such as osmolyte production, antioxidant enzyme activities (APX, SOD, CAT) and expression of drought-responsive genes (P5CS, BADH and CAT) in cluster bean were studied. It has been observed that P. stutzeri AK17 inoculation significantly enhanced the osmolyte accumulation under drought stress as compared to uninoculated plants. Decrease in the antioxidant enzyme activities in the P. stutzeri AK17-treated plants under severe stress suggests an efficient ROS homeostasis. Gene expression study revealed an upregulation of P5CS and BADH gene, while downregulation of the CAT gene on the 12th day of drought stress, which is correlated with the biochemical results. These findings indicate that there is some crosstalk between various defence mechanisms, and P. stutzeri AK17 has an important role in enhancing the defence systems. Therefore, the present work demonstrates the potential of P. stutzeri AK17 as a bioinoculant for enhancing drought tolerance in cluster bean under controlled greenhouse conditions, and future studies are required to evaluate its performance under field conditions for broader agricultural applicability.

Citations (0)

Mentions (0)

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Plant Science

Field

Agricultural and Biological Sciences

Domain

Life Sciences

Confidence Score

53%

Source

Scholar Data Model