Salinity is one of the most important abiotic stress factors affecting wheat production. Salt in the soil is a major environmental stressor that can affect the bacterial community in the rhizosphere of wheat. The bacteria in the plant’s rhizosphere promote growth and stress tolerance, which vary by variety and location. Nevertheless, the soil harbors some of the most diverse microbial communities, while the rhizosphere selectively recruits according to the needs of plants in a complex harmonic regulation. The microbial composition and diversity under normal and saline conditions were assessed by comparing the rhizosphere of wheat with soil using 16S rRNA gene amplicon sequencing, highlighting the number of operational taxonomic units (OTUs). Taxonomic analyzes showed that the bacterial community was predominantly and characteristically composed of the phyla Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Verrucomicrobia, and Fibrobacteres, representing the usual microbial profile for the rhizosphere of wheat. Idiomarinaceae, Rheinheimera, Halomonas, and Pseudomonas (a strain of Proteobacteria), together with Gracilibacillus (a strain of Firmicutes Bacilli), were recognized as microbial signatures for the rhizosphere microbiome under saline conditions. This was observed even with unchanged soil type and genotype. These patterns occurred despite the same soil type and genotype, with salinity being the only variable. The collective action of these bacterial phyla in the rhizosphere not only improves nutrient availability but also induces systemic resistance in the plants. This synergistic effect improves plant resistance to salt stress and supports the development of salt-tolerant wheat varieties. These microbial signatures could improve our understanding of plant–microbe interactions and support the development of microbiome-based solutions for salt stress.

Wheat is one of the most important cereal crops and an important source of food for billions of people worldwide. However, drought stress can pose a real threat to its productivity and lead to significant yield losses, especially in Egypt. The rhizospheric microbiome of wheat can play an important role in drought stress and help wheat to respond to this abiotic stress. Understanding this microbiome is therefore also important to improve drought stress resilience and productivity. In this study, a metagenomic analysis was performed to investigate how the composition and diversity of microbial communities associated with the wheat rhizosphere change under drought. Taxonomic and phylogenetic analyses revealed a shift in microbial abundance, with Actinobacteria, Bacteroidetes, Proteobacteria and Verrucomicrobia being the four most abundant phyla of the ethnic microbiota. Remarkably, other classes, including Alphaproteobacteria and Cytophagia, were significantly enriched under drought, which could be a promising enhancement of plant stress altruism. Differential abundance analysis showed that the control samples had higher abundance of microbial taxa such as OD1, WS2, Chlorobi, ABY1 and SHA-109 compared to the drought-treated genotypes. Functional prediction analysis using PICRUSt showed that an uncharacterized ATP-binding protein within the AAA + superfamily is overrepresented under drought conditions. This suggests that these genes may play a role in stress adaptation, possibly via energy-dependent regulation of cellular processes involved in plant survival. Our results expand our understanding of the complexity of responses of the wheat rhizosphere microbiome to drought and have practical implications for the development of microbial target combinations to improve wheat tolerance and productivity in the context of climate change challenges.

Rhizosphere microbiome engineering is a promising approach that can enhance crop resilience and input use efficiency by redirecting plant–microbe–soil interactions toward predictable functions. Here, we review the mechanistic bases underlying rhizosphere assembly and stability, including root exudate-mediated selection, priority effects, keystone taxa, and metabolite-driven signaling, and connect these principles to proposed design rules for microbial inoculants. We present a generalizable Design–Build–Test–Learn (DBTL) framework for engineering synthetic microbial consortia, covering trait-to-module mapping (nutrient acquisition, phytohormone modulation, ACC deaminase activity, stress-protective metabolites, and biocontrol), compatibility screening, minimal yet robust community architectures, and iterative optimization driven by multi-omics and high-throughput phenotyping. Translation to field settings is framed as an engineering challenge defined by formulation and administration limitations, including carrier type, seed coating and encapsulation methods, shelf life, strain invasiveness, and permanence of colonization amid environmental diversity. We also summarize how integrative measurement pipelines (amplicon and shotgun sequencing, transcriptomics, metabolomics, and network or causal analyses) can advance microbiome studies from correlation to actionability. We describe how precision agriculture (sensors, remote sensing, and variable-rate inputs) and AI/ML (split-sample comparisons, transfer learning, and active learning) approaches can accelerate strain discovery, mixture optimization, and adaptive experimentation, driven by the need for stringent controls, metadata-rich reporting, and cross-site comparability. Use cases focus on stress conditions (drought, salinity, thermal extremes, and biotic stress) to demonstrate how microbial functions translate to agronomic outcomes and to highlight critical bottlenecks for reproducible, scalable microbiome products.

Maize-Teosinte hybrids are of significant interest to maize breeders as a resource of genetic diversity during the maize domestication process as a genetic pool for maize improvement. This study examines the genetic diversity and population structure of 16 Zea mexicana populations which are currently active in Zea breeding programs in Egypt using Random Amplified Polymorphic DNA (RAPD) and Amplified Fragment Length Polymorphism (AFLP) markers. RAPD analysis (14 primers) produced 141 bands; out of which, 102 (72.3%) were polymorphic. On the other hand, AFLP (5 primer combinations) yielded 276 peaks including 267 (96.7%) polymorphic ones with an average of 53.4 peaks per primer combination. A total of 11 unique RAPD markers were created by 6 primers and identified 8 genotypes. The five primer combinations generated 56 unique amplicons that successfully distinguished 12 out of the 16 genotypes tested. Furthermore, the number of observed alleles (Na), effective multiplex ratio (EMR), and polymorphic information content (PIC) indices showed higher values for AFLP (2.00, 53.4, and 0.21) than for RAPD (1.67, 7.3, and 0.15). Cluster analysis based on Nei and Li genetic distance and an Unweighted Pair Group Method with Arithmetic Mean (UPGMA) revealed 5 main clusters representing the 16 Zea mexicana confirming the population structure analysis obtained. High variability of the studied teosinte genotypes using RAPD and AFLP markers will provide valuable tools for Zea mexicana breeding programs in Egypt.

Climate change causes an increase in the intensity of adverse abiotic and biotic stresses that could severely threaten agriculture production and food security including production, access, and prices. The world's population is anticipated to reach 9.8 billion by 2050, while food production would decline by 20%. The risk of continuous change in the environment has attracted the attention of plant scientists, who are using all available technologies to enhance crop quality and yield. Omics approaches are crucial for studying stress tolerance mechanisms and exploring candidate genes. Several efforts have been made to face these emerging challenges using traditional breeding, genetically modified organisms, and genome editing. Over the last decade, the integration of CRISPR/Cas genome editing into modern breeding programs has had a great impact on crop improvement by targeting precise changes to genomes. Genome editing is a good candidate for developing beneficial climate-resilient crops targeting biotechnological tools. Recently, new techniques in genome editing have been developed, including epigenome modifiers, and base and prime editing which are promising developments for improving plant performance and crop productivity. This chapter unravels the whole picture of the application of genome editing to address climate change and improve crops. <!----> <!----> <!----> <!---->

Drought stress severely damages the growth and development of wheat and leads to lower crop production. The application of plant growth-promoting rhizobacteria (PGPR) is a sustainable approach that enhances plant tolerance to drought. This study investigated whether different bacterial isolates could promote wheat growth under drought conditions. A total of 73 bacterial isolates were obtained from the rhizosphere of Egyptian wheat cultivars, 30 of which exhibited ACC deaminase activity. The isolates were selected based on various PGPR characteristics, including phosphate solubilization, siderophore production, nitrogen fixation, indole-3-acetic acid production, biofilm formation, and antagonistic abilities. The active ACC colonies were screened for these traits and based on in vitro promotion of wheat plant growth, root inoculum from four wheat plants was used and grown under drought conditions. The percentage yield of wheat plants increased in the weight of wheat plants, while in total biomass it was found that the treatments showed significant differences compared to the control. The most effective ACC was from the wheat isolate B. subtilis. The bacterial types were identified at the genus level by sequencing the 16s rRNA gene. In conclusion, this research suggests PGPR such as V. paradoxus and K. oxytoca have the potential to reduce the effects of drought stress in Egyptian wheat cultivars.