RESUMEN
Climate change gives rise to numerous environmental stresses, including soil salinity. Salinity/salt stress is the second biggest abiotic factor affecting agricultural productivity worldwide by damaging numerous physiological, biochemical, and molecular processes. In particular, salinity affects plant growth, development, and productivity. Salinity responses include modulation of ion homeostasis, antioxidant defense system induction, and biosynthesis of numerous phytohormones and osmoprotectants to protect plants from osmotic stress by decreasing ion toxicity and augmented reactive oxygen species scavenging. As most crop plants are sensitive to salinity, improving salt tolerance is crucial in sustaining global agricultural productivity. In response to salinity, plants trigger stress-related genes, proteins, and the accumulation of metabolites to cope with the adverse consequence of salinity. Therefore, this review presents an overview of salinity stress in crop plants. We highlight advances in modern biotechnological tools, such as omics (genomics, transcriptomics, proteomics, and metabolomics) approaches and different genome editing tools (ZFN, TALEN, and CRISPR/Cas system) for improving salinity tolerance in plants and accomplish the goal of "zero hunger," a worldwide sustainable development goal proposed by the FAO.
RESUMEN
Pantoea ananatis is a major pathogen that causes the new bacterial blight in rice, and its symptoms very similar to rice bacterial blight. Therefore, there is a dire need for an accurate and rapid method for detecting P. ananatis. In this study, an early and rapid visual detection method for P. ananatis was established. Using GyrB gene as the target sequence, an innovative recombinase-aided amplification detection system integrated with a lateral flow dipstick (RAA-LFD) was constructed. The optimized RAA-LFD detection method can be initiated at body temperature and does not rely on precise instruments. It does not require DNA extraction and can be used directly with plant tissue fluids. The results can be visualized after 10 minutes of amplification. The specificity and sensitivity tests showed that the RAA-LFD method could detect P. ananatis, whereas other common plant pathogens were not detected, and its detection sensitivity for P. ananatis DNA reached 100 copies/µL. The detection of diseased tissues indicated that this method could accurately detect P. ananatis in artificially inoculated rice tissues in the early stages of infection before symptoms. The RAA-LFD detection system established in this study is simple and fast, with visual results, excellent specificity, and high sensitivity. It is semi-quantitative and should be used for the early detection and rapid field diagnosis of new leaf blight, which provides technical support for the early warning and real-time detection of field samples.