Omics-Based Insights into Plant–Microbe Interactions for Crop Improvement
Authors: Nalini Salvadi and Mohammad Imran Mir
Journal Name: Plant Science Review
DOI: https://doi.org/10.51470/PSR.2024.05.01.29
Keywords: Plant–microbe interactions, omics technologies, crop improvement, microbiome engineering, stress tolerance
Abstract
The integration of omics technologies—genomics, transcriptomics, proteomics, metabolomics, and metagenomics—has revolutionized our understanding of plant–microbe interactions, offering profound insights for sustainable crop improvement. These multidimensional approaches unravel the complex molecular dialogues between plants and associated microorganisms, including beneficial rhizobacteria, mycorrhizal fungi, and endophytes, which collectively influence plant health, stress tolerance, and productivity. Omics-based analyses facilitate the identification of microbial taxa and plant genes involved in nutrient acquisition, disease resistance, and abiotic stress mitigation, thereby enabling the development of bioinoculants, bio stimulants, and genetically enhanced crops. Functional genomics and meta transcriptomics uncover gene expression patterns in both plants and microbes during interaction phases, while proteomics and metabolomics elucidate the active proteins and metabolites that mediate symbiosis or antagonism. This holistic understanding supports precision agriculture by guiding microbiome engineering and breeding strategies aimed at enhancing crop yield and resilience in the face of climate variability, resource limitations, and pathogen pressures.
INTRODUCTION
The global demand for sustainable agricultural practices has intensified in recent decades due to increasing population pressure, climate change, and environmental degradation caused by intensive farming. Conventional agriculture, reliant on chemical fertilizers and pesticides, has reached its ecological limits, necessitating the exploration of innovative strategies for crop improvement. One such promising avenue is the study of plant–microbe interactions, which play a pivotal role in influencing plant growth, health, and productivity [1]. Beneficial microorganisms, including rhizobacteria, fungi, and endophytes, are known to enhance nutrient uptake, stimulate plant defense responses, and improve tolerance to biotic and abiotic stresses. Understanding these interactions at the molecular and ecological levels is critical to unlocking their potential for sustainable agriculture. With the advent of high-throughput technologies, omics sciences have emerged as transformative tools in plant and microbial research. Genomics, transcriptomics, proteomics, metabolomics, and metagenomics enable the comprehensive analysis of biological systems, offering a systems-level understanding of complex plant–microbe associations. These omics platforms facilitate the identification of key genes, proteins, and metabolites involved in mutualistic or antagonistic interactions [2]. Furthermore, they allow the monitoring of dynamic changes in response to environmental stimuli, plant development stages, or microbial colonization. Such integrative insights are essential for tailoring crop varieties and microbial consortia for enhanced agricultural performance.
Genomics provides a foundational understanding of the genetic blueprints of both plants and microbes involved in interactions. Whole-genome sequencing (WGS) of beneficial microbes enables the discovery of plant growth-promoting traits such as nitrogen fixation, phosphate solubilization, and phytohormone production. Similarly, sequencing plant genomes reveals genes that regulate microbial recognition, immune responses, and symbiotic compatibility. Comparative genomics between different microbial strains or plant cultivars can uncover the genetic basis of beneficial interactions, offering targets for crop breeding or microbial engineering [3]. Transcriptomics complements genomics by analyzing gene expression profiles during plant–microbe interactions. By identifying differentially expressed genes (DEGs) in plants and microbes under co-cultivation or stress conditions, researchers can elucidate signaling pathways, transcription factors, and defense mechanisms activated in response to microbial presence. RNA sequencing (RNA-seq) allows for the temporal analysis of gene expression dynamics, providing insights into how specific genes orchestrate colonization, resistance, or symbiosis over time [4]. These findings contribute to the rational design of microbial inoculants and genetically enhanced crops with improved compatibility. Proteomics and metabolomics further deepen the understanding of functional interactions by capturing the active proteins and metabolites that drive physiological changes. Proteomics reveals the post-translational modifications and protein–protein interactions involved in microbe-induced pathways, while metabolomics identifies key secondary metabolites such as flavonoids, phytoalexins, and volatile compounds that mediate communication and defense. These approaches are particularly useful in detecting subtle molecular changes that are not apparent at the transcript level, enabling a more complete picture of the interaction landscape. Finally, metagenomics and meta transcriptomics provide ecosystem-level insights into the structure and function of plant-associated microbial communities [5]. These approaches bypass the need for culturing, allowing for the analysis of complex microbiomes in rhizosphere, phyllo sphere, and endosphere niches. By comparing microbial diversity and gene expression patterns across different environmental conditions, plant species, or management practices, researchers can identify beneficial microbes and functions that promote plant health. This knowledge paves the way for microbiome engineering, where tailored microbial consortia are designed to improve soil fertility, disease resistance, and stress resilience in crops.
The Foundation of Plant–Microbe Interactions
Plant–microbe interactions form the ecological and molecular basis of sustainable agriculture. Plants interact with a wide array of microorganisms—ranging from mutualistic and commensal to pathogenic—that colonize their rhizosphere, phyllosphere, and endosphere [6]. These relationships influence nutrient acquisition, growth regulation, and stress responses. The beneficial microbes, such as rhizobacteria and mycorrhizal fungi, help in solubilizing nutrients, fixing atmospheric nitrogen, and producing phytohormones that promote plant development. Understanding these interactions at the systems level is critical for developing resilient crop systems. Beneficial microbial partnerships can be enhanced through targeted breeding or microbial consortia, once the mechanisms behind them are uncovered [7]. With omics technologies, researchers can dissect the complex genetic, transcriptomic, proteomic, and metabolic landscapes that govern these relationships. This knowledge is now being integrated into plant science to boost productivity and reduce reliance on chemical inputs.
Genomics: Mapping the Blueprint of Plant–Microbe Symbiosis
Genomics provides a comprehensive view of the DNA-level architecture of plants and their associated microbes. Whole-genome sequencing (WGS) enables the identification of genes responsible for traits such as nitrogen fixation in microbes or disease resistance in plants. Advances in sequencing technology have dramatically reduced costs, allowing researchers to sequence multiple microbial genomes and plant cultivars efficiently. Genomic comparisons across microbial strains help identify plant-beneficial traits such as siderophore production, indole-3-acetic acid (IAA) synthesis, and phosphate solubilization. Similarly, plant genomics reveals receptor-like kinases and nodulation factors that facilitate communication with microbes. These insights provide a foundation for targeted genetic modifications or marker-assisted breeding strategies that improve plant–microbe compatibility and performance [8].
Transcriptomics: Decoding the Language of Genes
Transcriptomics focuses on analyzing gene expression patterns under different interaction scenarios. RNA sequencing (RNA-seq) allows for real-time observation of transcriptional changes in both plants and microbes during colonization or stress. This layer of information reveals which genes are upregulated or silenced as a response to microbial presence. These insights are essential for identifying regulatory networks, signaling molecules, and defensive responses triggered during plant–microbe interactions. For instance, in the presence of beneficial rhizobacteria, genes related to growth and immunity may be activated, while stress-related pathways may be downregulated [9]. Transcriptomics bridges the gap between genomic potential and actual biological activity, guiding functional validation studies.
Proteomics: Unveiling the Functional Machinery
Proteomics complements genomics and transcriptomics by focusing on the proteins—the active agents in cellular processes. Unlike genes or mRNAs, proteins carry out structural, enzymatic, and signaling roles directly involved in plant–microbe communication. Mass spectrometry-based proteomics allows identification of differentially expressed proteins during interaction stages [10]. By studying the post-translational modifications and protein–protein interactions, researchers can understand how plant cells respond to microbial elicitors and how microbes modulate their own proteins to evade or establish compatibility. Proteomics also helps in identifying biomarkers for improved plant varieties, contributing to precision agriculture strategies and tailored crop improvement programs.
Metabolomics: Profiling Biochemical Responses
Metabolomics investigates the complete set of metabolites—small molecules such as sugars, amino acids, and secondary metabolites—produced in plant–microbe systems. These molecules often act as signaling compounds or defense agents that shape the outcome of plant–microbe interactions. For instance, flavonoids secreted by plant roots can attract symbiotic microbes or repel pathogens. Through technologies like gas chromatography-mass spectrometry (GC-MS) or nuclear magnetic resonance (NMR), metabolomics helps identify changes in metabolic profiles in response to microbial inoculation. This allows researchers to trace biochemical pathways activated during beneficial interactions, such as those leading to increased production of phytoalexins or osmoprotectants under stress conditions [11]. Metabolomics offers a dynamic picture of how plant metabolism is influenced by microbial presence.
Metagenomics and the Plant Microbiome Landscape
Metagenomics bypasses the need to culture microbes and directly sequences DNA from environmental samples like soil or root-associated microbiomes. This allows comprehensive profiling of microbial communities inhabiting the rhizosphere, phyllosphere, and endosphere. These communities significantly impact nutrient cycling, pathogen suppression, and plant hormone modulation. By analyzing the taxonomic and functional diversity of microbiomes, metagenomics identifies candidate organisms and functional genes beneficial for plant health [12]. For example, genes linked to nitrogen metabolism or antibiotic production may be enriched in healthy plant microbiomes. Such insights pave the way for designing synthetic microbial communities tailored to specific crops and environments.
Metatranscriptomics: Functional Insight into Microbial Consortia
Metatranscriptomics expands on metagenomics by revealing which microbial genes are actively expressed under field or greenhouse conditions. This approach identifies functional contributions of microbiomes to the host plant’s physiology in real-time. By analyzing environmental RNA, researchers can determine which microbial genes are induced during root colonization or stress mitigation. This technology has proven crucial in understanding the dynamic behavior of microbial communities under fluctuating environmental conditions [13]. It also helps identify previously unknown pathways involved in nutrient solubilization or plant defense activation, contributing to the functional annotation of microbial genomes. Metatranscriptomics offers a systems-level approach to decipher how microbial activity shapes plant phenotypes.
Beneficial Traits Mediated by Microbial Interactions
Beneficial plant–microbe interactions contribute to key agronomic traits such as enhanced growth, disease resistance, and stress tolerance. Microbial mechanisms such as nitrogen fixation, phosphate solubilization, and ACC deaminase production directly impact plant nutrition and growth regulation. Other microbes induce systemic resistance, reducing disease severity without the need for chemical pesticides [14]. Harnessing these traits through omics-informed strategies allows targeted selection of microbial inoculants with high potential for field applications. Omics data help validate which microbial genes or pathways are truly functional and beneficial under agricultural conditions. This ensures consistent performance and reduces variability in microbial applications.
Plant Immune Responses and Microbial Recognition
Plants possess an intricate immune system that discriminates between pathogenic and beneficial microbes. Pattern recognition receptors (PRRs) on plant surfaces detect microbial-associated molecular patterns (MAMPs), initiating basal defense responses. However, beneficial microbes can suppress or bypass these responses to establish symbiosis. Omics analyses have revealed various immune regulatory genes and signaling cascades modulated during microbial colonization. Transcriptomic and proteomic studies help identify how plants reprogram their defense machinery to accommodate symbionts without compromising overall immunity [15]. Understanding this balance is key for engineering crops with enhanced microbial compatibility and disease resistance.
Microbial Signaling Molecules in Plant Communication
Microbes produce a wide range of signaling molecules such as lipo-chitooligosaccharides (LCOs), quorum-sensing compounds, and volatile organic compounds (VOCs) that influence plant physiology. These signals can stimulate root branching, activate defense genes, or attract beneficial insects. Identifying these molecules and their biosynthetic pathways is crucial for functional annotation. Omics approaches—especially metabolomics and proteomics—enable detection of these signals and help map their interaction with plant receptors [16]. These insights can be used to screen for elite microbial strains with stronger signaling capabilities, which can be integrated into biofertilizer and biopesticide development pipelines.
Crop Breeding Using Omics Markers
Omics-generated markers such as SNPs (Single Nucleotide Polymorphisms) or DEGs (Differentially Expressed Genes) are invaluable tools in crop improvement. These markers help breeders identify plant genotypes with superior traits such as enhanced symbiosis, disease resistance, or nutrient efficiency. Genomics-assisted breeding reduces the need for trial-and-error phenotyping. Combining omics data with traditional breeding programs enables the development of elite crop varieties optimized for interaction with beneficial microbes [17]. Marker-assisted selection (MAS) and genomic selection (GS) strategies guided by omics insights are now becoming standard in modern plant breeding.
Microbiome Engineering for Crop Resilience
Microbiome engineering involves the deliberate manipulation of plant-associated microbial communities to improve plant performance. This includes designing synthetic microbial consortia, modifying microbial genes, or altering host plant traits to favor beneficial colonization. Omics data guide this process by identifying key microbial species and functional genes. The integration of metagenomics, metabolomics, and transcriptomics allows prediction of microbial interactions, stability, and adaptability in various environments [18]. This precision enables tailored microbiome solutions for specific crops, soil types, and climate conditions, making microbiome engineering a powerful tool for climate-smart agriculture.
Omics in Biocontrol Agent Discovery
Biocontrol agents are microbes that suppress plant pathogens through competition, parasitism, or induction of plant defenses. Omics technologies aid in identifying potential biocontrol strains by profiling their genomes for antimicrobial compounds, siderophores, and enzymes like chitinases or glucanases. Metabolomic studies further identify bioactive metabolites produced by these microbes, ensuring their efficacy and safety [19]. Combining multi-omics layers provides a comprehensive strategy for discovering, testing, and formulating novel biocontrol products, reducing dependency on synthetic pesticides.
Abiotic Stress Tolerance and Microbial Synergy
Abiotic stresses such as drought, salinity, and heavy metal toxicity severely affect crop yields. Beneficial microbes mitigate these stresses by producing stress-alleviating compounds like exopolysaccharides, osmolytes, and heat-shock proteins. Omics data reveal how microbial inoculation triggers stress-responsive genes and metabolites in host plants. This knowledge facilitates the selection of microbial strains best suited for specific stress conditions and plant species [20]. Moreover, breeding programs can target plant genes involved in synergistic responses to microbe-assisted stress mitigation, paving the way for climate-resilient agriculture.
Challenges and Future Prospects in Omics-Driven Research
Despite the promising insights, integrating omics data remains a complex task. The sheer volume of data, variability in field conditions, and lack of standard pipelines pose significant challenges. [21] Moreover, translating lab-based results into real-world applications requires interdisciplinary collaboration. Future research must focus on refining bioinformatics tools, standardizing protocols, and incorporating AI and machine learning for predictive modeling. As multi-omics integration improves, the vision of precision agriculture—where microbial and plant genetics are co-optimized—will become increasingly attainable.
Conclusion
The integration of omics technologies into the study of plant–microbe interactions represents a transformative approach to understanding and enhancing crop systems. Genomics, transcriptomics, proteomics, metabolomics, and metagenomics have collectively provided unprecedented insights into the molecular and biochemical foundations of these complex relationships. These technologies enable a holistic perspective on how plants interact with their associated microbial communities, revealing key genes, regulatory networks, and functional pathways that determine plant health, productivity, and stress tolerance. This systems biology framework facilitates the discovery of beneficial microbial strains and plant traits that can be harnessed for improved crop outcomes. As global agriculture faces the twin challenges of climate change and resource limitations, omics-guided strategies offer sustainable alternatives to traditional practices. Through the identification of microbial bioeffectors, regulatory plant genes, and synergistic biochemical pathways, scientists can develop bioinoculants, plant varieties, and integrated systems tailored to specific agroecological contexts. Additionally, the application of omics data in breeding programs, microbiome engineering, and biocontrol development accelerates the transition toward precision agriculture. By decoding how plants and microbes communicate and adapt, omics technologies provide tools to build resilient cropping systems that reduce reliance on chemical inputs and enhance ecological balance, and manipulate plant–microbe systems for desired outcomes. Interdisciplinary collaboration among molecular biologists, agronomists, microbiologists, and data scientists is essential to translate laboratory insights into field-level applications. With sustained research, investment, and innovation, omics-based plant–microbe studies hold the key to revolutionizing global agriculture—ushering in an era of productivity, sustainability, and resilience for future food systems.
References
- Berendsen, R. L., Pieterse, C. M. J., & Bakker, P. A. H. M. (2012). The rhizosphere microbiome and plant health. Trends in Plant Science, 17(8), 478–486.
- Bulgarelli, D., Schlaeppi, K., Spaepen, S., Van Themaat, E. V. L., & Schulze-Lefert, P. (2013). Structure and functions of the bacterial microbiota of plants. Annual Review of Plant Biology, 64, 807–838.
- Sessitsch, A., Pfaffenbichler, N., & Mitter, B. (2019). Microbiome applications from lab to field: Facing complexity. Trends in Plant Science, 24(3), 194–198.
- Zhang, H., Murzello, C., Sun, Y., Kim, M.-S., Xie, X., Jeter, R. M., & Kloepper, J. W. (2010). Choline and osmotic-stress tolerance induced in Arabidopsis by a plant growth-promoting rhizobacterium. Plant Physiology, 154(1), 347–360.
- Trivedi, P., Leach, J. E., Tringe, S. G., Sa, T., & Singh, B. K. (2020). Plant–microbiome interactions: From community assembly to plant health. Nature Reviews Microbiology, 18(11), 607–621.
- Delmotte, N., Knief, C., Chaffron, S., Innerebner, G., Roschitzki, B., Schlapbach, R., & Vorholt, J. A. (2009). Community proteogenomics reveals insights into the physiology of phyllosphere bacteria. PNAS, 106(38), 16428–16433.
- Vurukonda, S. S. K. P., Vardharajula, S., Shrivastava, M., & SkZ, A. (2016). Enhancement of drought stress tolerance in crops by plant growth promoting rhizobacteria. Microbiological Research, 184, 13–24.
- Pérez-Jaramillo, J. E., Carrión, V. J., Bosse, M., Ferrão, L. F. V., De Hollander, M., Garcia, A. A. F., & Mendes, R. (2017). Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits. ISME Journal, 11, 2244–2257.
- Mendes, R., Garbeva, P., & Raaijmakers, J. M. (2013). The rhizosphere microbiome: Significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiology Reviews, 37(5), 634–663.
- Lugtenberg, B., & Kamilova, F. (2009). Plant-growth-promoting rhizobacteria. Annual Review of Microbiology, 63, 541–556.
- Edwards, J., Johnson, C., Santos-Medellín, C., Lurie, E., Podishetty, N. K., Bhatnagar, S., & Dangl, J. L. (2015). Structure, variation, and assembly of the root-associated microbiomes of rice. PNAS, 112(8), E911–E920.
- Zgadzaj, R., Garrido-Oter, R., Jensen, D. B., Koprivova, A., Schulze-Lefert, P., & Radutoiu, S. (2016). Root nodule symbiosis in Lotus japonicus drives the establishment of distinctive rhizosphere, root, and nodule bacterial communities. PNAS, 113(49), E7996–E8005.
- Nannipieri, P., Ascher, J., Ceccherini, M. T., Landi, L., Pietramellara, G., & Renella, G. (2008). From genes to ecosystems: A conceptual framework for the distribution and functioning of microorganisms in soil. Soil Biology & Biochemistry, 40(5), 1027–1040.
- Borriss, R. (2015). Bacillus, a plant-beneficial genus: New insights into the biology of plant growth promotion and biocontrol. Environmental and Experimental Botany, 114, 1–2.
- Sasse, J., Martinoia, E., & Northen, T. (2018). Feed your friends: Do plant exudates shape the root microbiome? Trends in Plant Science, 23(1), 25–41.
- Mitter, B., Pfaffenbichler, N., Flavell, R., Compant, S., Antonielli, L., Petric, A., & Sessitsch, A. (2017). A new approach to modify plant microbiomes and traits by introducing beneficial bacteria at flowering into progeny seeds. Frontiers in Microbiology, 8, 11.
- Turner, T. R., James, E. K., & Poole, P. S. (2013). The plant microbiome. Genome Biology, 14(6), 209.
- Bakker, P. A., Pieterse, C. M., & Van Loon, L. C. (2007). Induced systemic resistance by fluorescent Pseudomonas spp. Phytopathology, 97(2), 239–243.
- Zhalnina, K., Louie, K. B., Hao, Z., Mansoori, N., da Rocha, U. N., Shi, S., & Brodie, E. L. (2018). Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nature Microbiology, 3, 470–480.
- Kolton, M., Frenkel, O., Elad, Y., & Cytryn, E. (2014). Potential role of root exudates in recruiting beneficial soil bacteria. Plant and Soil, 379(1-2), 1–16.
- Chaparro, J. M., Badri, D. V., & Vivanco, J. M. (2014). Rhizosphere microbiome assemblage is affected by plant development. ISME Journal, 8(4), 790–803.