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Plasma treatment has emerged as a promising tool for manipulating plant microbiomes and metabolites. This review explores the diverse applications and effects of plasma on these biological systems. It is hypothesized that plasma treatment will not induce substantial changes in the composition of plant microbiomes or the concentration of plant metabolites. We delve into the mechanisms by which plasma can regulate microbial communities, enhance antimicrobial activity, and recruit beneficial microbes to mitigate stress. Furthermore, we discuss the optimization of plasma parameters for effective microbiome interaction and the role of plasmids in plant–microbe interactions. By characterizing plasmidome responses to plasma exposure and investigating transcriptional and metabolomic shifts, we provide insights into the potential of plasma as a tool for engineering beneficial plant–microbe interactions. The review presented herein demonstrates that plasma treatment induces substantial changes in both microbial community composition and metabolite levels, thereby refuting our initial hypothesis. Finally, we integrate plasmidome, transcriptome, and metabolome data to develop a comprehensive understanding of plasma’s effects on plant biology and explore future perspectives for agricultural applications. 

Rhizosphere microbiome exerts a significant role in plant health, influencing nutrient availability, disease resistance, and overall plant growth. Establishing a robust and efficient nodulation process is essential for optimal nitrogen fixation in legumes like soybeans. Different soybean genotypes exhibit variations in their rhizosphere microbiome, potentially impacting nitrogen fixation through nodulation. However, a detailed understanding of how specific soybean genotypes influence rhizosphere microbial communities and nodulation patterns remains limited. Our study aims to investigate the relationship between rhizosphere microbial abundance and plant growth in four soybean genotypes. We evaluated plant growth parameters, including biomass, leaf area, and stomatal conductance, and identified significant genotypic differences in nodulation. Specifically, genotypes PI 458505 and PI 603490 exhibited high levels of nodulation, while PI 605839A and PI 548400 displayed low nodulation. 16S rRNA gene amplicon sequencing revealed diverse bacterial communities in the rhizosphere, with Proteobacteria as the dominant phylum. High-nodulation genotypes harbored more diverse microbial communities enriched with Actinobacteria and Acidobacteriota, while low-nodulation genotypes showed higher abundances of Firmicutes and Planctomycetota. Alpha and beta diversity analyses confirmed distinct microbial community structures between high- and low-nodulation groups. Our findings suggest that the rhizosphere microbiome significantly influences soybean growth and nodulation, highlighting the potential for genotype-driven strategies to enhance plant-microbe interactions and improve soybean productivity. 

Drought stress has a significant impact on agricultural productivity, affecting key crops such as soybeans, the second most widely cultivated crop in the United States. Endophytic and rhizospheric microbial diversity analyses were conducted with soybean plants cultivated during the 2023 growing season amid extreme weather conditions of prolonged high temperatures and drought in Louisiana. Specifically, surviving and non-surviving soybean plants were collected from two plots of a Louisiana soybean field severely damaged by extreme heat and drought conditions in 2023. Although no significant difference was observed between surviving and non-surviving plants in microbial diversity of the rhizosphere, obvious differences were found in the structure of the endophytic microbial community in root tissues between the two plant conditions. In particular, the bacterial genera belonging to Proteobacteria, Pseudomonas and Pantoea, were predominant in the surviving root tissues, while the bacterial genus Streptomyces was conspicuously dominant in the non-surviving (dead) root tissues. Co-occurrence patterns and network centrality analyses enabled us to discern the intricate characteristics of operational taxonomic units (OTUs) within endophytic and rhizospheric networks. Additionally, we isolated and identified bacterial strains that enhanced soybean tolerance to drought stresses, which were sourced from soybean plants under a drought field condition. The 16S rDNA sequence analysis revealed that the beneficial bacterial strains belong to the genera Acinetobacter, Pseudomonas, Enterobacter, and Stenotrophomonas. Specific bacterial strains, particularly those identified as Acinetobacter pittii and Pseudomonas sp., significantly enhanced plant growth metrics and reduced drought stress indices in soybean plants through seed treatment. Overall, this study advances our understanding of the soybean-associated microbiome structure under drought stress, paving the way for future research to develop innovative strategies and biological tools for enhancing soybean resilience to drought. 

Network centrality analyses have proven to be successful in identifying important nodes in diverse host–pathogen interactomes. The current study presents a comprehensive investigation of the human interactome and SARS-CoV-2 host targets. We first constructed a comprehensive human interactome by compiling experimentally validated protein–protein interactions (PPIs) from eight distinct sources. Additionally, we compiled a comprehensive list of 1449 SARS-CoV-2 host proteins and analyzed their interactions within the human interactome, which identified enriched biological processes and pathways. Seven diverse topological features were employed to reveal the enrichment of the SARS-CoV-2 targets in the human interactome, with closeness centrality emerging as the most effective metric. Furthermore, a novel approach called CentralityCosDist was employed to predict SARS-CoV-2 targets, which proved to be effective in expanding the pool of predicted targets. Pathway enrichment analyses further elucidated the functional roles and potential mechanisms associated with predicted targets. Overall, this study provides valuable insights into the complex interplay between SARS-CoV-2 and the host’s cellular machinery, contributing to a deeper understanding of viral infection and immune response modulation. 

Submerged plants can thrive entirely underwater, playing a crucial role in maintaining water quality, supporting aquatic organisms, and enhancing sediment stability. However, they face multiple challenges, including reduced light availability, fluctuating water conditions, and limited nutrient access. Despite these stresses, submerged plants demonstrate remarkable resilience through physiological and biochemical adaptations. Additionally, their interactions with microbial communities are increasingly recognized as pivotal in mitigating these environmental stresses. Understanding the diversity of these microbial communities is crucial for comprehending the complex interactions between submerged plants and their environments. This research aims to identify and screen microbes from submerged plant samples capable of producing 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase and to explore microbial diversity through metagenomic analysis. Microbes were isolated and screened for ACC deaminase production, and metagenomic techniques, including co-occurrence network analysis, were used to examine microbial diversity and interactions within the communities. ACC deaminase-producing microbes can significantly enhance plant metabolism under stress conditions. The identification of the culturable bacteria revealed that most of these microbes belong to the genera Pseudomonas, Bacillus, and Acinetobacter. A total of 177 microbial strains were cultured, with molecular identification revealing 79 reductant, 86 non-reductant, and 12 uncultured strains. Among 162 samples screened for ACC deaminase activity, 50 tested positive. To further understand microbial dynamics, samples were collected from both natural sources and artificial pond reservoirs to assess the impact of the location on flood-associated microbiomes in submerged plants. Metagenomic analysis was conducted on both the epiphytic and endophytic samples. By exploring the overall composition and dynamics of microbial communities associated with submerged plants, this research seeks to deepen our understanding of plant–microbe interactions in aquatic environments. The microbial screening helped to identify the diverse microbes associated with ACC deaminase activity in submerged plants and amplicon sequencing analysis paved the way towards identifying the impact of the location in shaping the microbiome and the diversity associated with endophytic and epiphytic microbes. Co-occurrence network analysis further highlighted the intricate interactions within these microbial communities. Notably, ACC deaminase activity was observed in plant-associated microbes across different locations, with distinct variations between epiphytic and endophytic populations as identified through co-occurrence network analysis. 

Salt marshes are highly dynamic and biologically diverse ecosystems that serve as natural habitats for numerous salt-tolerant plants (halophytes). We investigated the bacterial communities associated with the roots and leaves of plants growing in the coastal salt marshes of the Bayfront Beach, located in Mobile, Alabama, United States. We compared external (epiphytic) and internal (endophytic) communities of both leaf and root plant organs. Using 16S rDNA amplicon sequencing methods, we identified 10 bacterial phyla and 59 different amplicon sequence variants (ASVs) at the genus level. Bacterial strains belonging to the phyla Proteobacteria, Bacteroidetes, and Firmicutes were highly abundant in both leaf and root samples. At the genus level, sequences of the genus Pseudomonas were common across all four sample types, with the highest abundance found in the leaf endophytic community. Additionally, Pantoea was found to be dominant in leaf tissue compared to roots. Our study revealed that plant habitat (internal vs. external for leaves and roots) was a determinant of the bacterial community structure. Co-occurrence network analyses enabled us to discern the intricate characteristics of bacterial taxa. Our network analysis revealed varied levels of ASV complexity in the epiphytic networks of roots and leaves compared to the endophytic networks. Overall, this study advances our understanding of the intricate composition of the bacterial microbiota in habitats (epiphytic and endophytic) and organs (leaf and root) of coastal salt marsh plants and suggests that plants might recruit habitat- and organ-specific bacteria to enhance their tolerance to salt stress.