# Grasping Molecular Biology Mechanisms to Optimize Plant Resistance and Advance Microbiome Role Against Phytonematodes

**Authors:** Mahfouz M. M. Abd-Elgawad

PMC · DOI: 10.3390/ijms27041744 · International Journal of Molecular Sciences · 2026-02-11

## TL;DR

This review explores how plant microbiomes and molecular strategies can enhance plant resistance to parasitic nematodes and improve crop management.

## Contribution

The paper introduces novel microbiome-based strategies and genetic engineering techniques to optimize plant resistance against phytonematodes.

## Key findings

- CRISPR/Cas9 successfully knocks out genes in rice and cotton to confer nematode resistance without yield loss.
- Microbiome inoculants and systemic acquired resistance (SAR) mediated by salicylic acid can prime plant defenses.
- Advanced molecular tools are needed to distinguish microbiome strains with divergent functional traits.

## Abstract

Plant-parasitic nematodes (PPNs) cause big crop losses globally. Safe/reliable methods for their durable management strategies can harness various beneficial relationships among the plant immune system and related microbiomes. Molecular mechanisms basic to these relations reveal wide arrays of significant roles for plant-healthy growth. This review focuses on such relations of microbiomes to prime and immunize plants against PPNs. It also highlights molecular issues facing PPN-resistant varieties with possible solutions such as genetic breeding/engineering, grafting, PPN-antagonistic root exudates, and novel resistant cultivars. These issues call for optimal uses of various widespread groups of microbiomes. Related plant signaling hormones and transcription factors that regulate gene expression and modulate nematode-responsive genes to ease positive/negative adaptation are presented. Exploring PPN-resistance genes, their activation mechanisms, and signaling networks offers a holistic grasp of plant defense related to biotic/abiotic factors. Such factors relevant to systemic acquired resistance (SAR) via plant–microbe interactions to manage PPNs are stressed. The microbiomes can be added as inoculants and/or steering the indigenous rhizosphere ones. Consequently, SAR is mediated by the accumulation of salicylic acid and the subsequent expression of pathogenesis-related genes. To activate SAR, adequate priming and induction of plant defense against PPNs would rely on closely linked factors. They mainly include the engaged microbiome species/strains, plant genotypes, existing fauna/flora, compatibility with other involved biologicals, and methods/rates of the inoculants. To operationalize improved plant resistance and the microbiome’s usage, novel actionable insights for research and field applications are necessary. Synthesis of adequate screening techniques in plant breeding would better use multiple parameters (molecular and classical ones)-based ratings for PPN-host suitability designation. Sound statistical analyses and interpretation approaches can better identify genotypes with high-level, stable resistance to PPNs than the commonly used ones. Linking molecular mechanisms to consistent field relevance can be progressed via dissemination of many advanced techniques. The CRISPR/Cas9 system has been effective in knocking out both the OsHPP04 gene in rice to confer resistance against Meloidogyne graminicola and the GhiMLO3 gene in cotton to minimize the Rotylenchulus reniformis reproduction. Its genetic modifications in crops synthesized “transgene-free” PPN-resistant plants without decreased growth/yield. Characterizing microbiome species/strains needed to prime and immunize plants requires better molecular tools for fine-scale taxonomic resolution than the common ones used. The former can distinguish closely related ones that exhibit divergent phenotypes for key attributes like stability and production of enzymes and secondary metabolites. As PPN-control strategies via tritrophic interactions are more sensitive to the relevant settings than chemical nematicides, it is suggested herein to test these settings on a case-by-case basis to avoid erratic/contradictory results. Moreover, expanding the use of automated systems to expedite detection/count processes of PPN and related microbes with objectivity/accuracy is discussed. When PPNs and their related microbial distribution patterns were modeled, more aspects of their field distributions were discovered in order to optimize their integrated management. Hence, the feasibility of site-specific microbiome application in PPN–hotspot infections can be evaluated. The main technical challenges and controversies in the field are also addressed herein. Their conceptual revision based on harnessing novel techniques/tools is direly needed for future clear trends. This review also engages raising growers’ awareness to leverage such strategies for enhancing plant resistance and advancing the microbiome role. Microbiomes enjoy wide spectrum efficacy, low fitness cost, and inheritance to next generations in durable agriculture.

## Full-text entities

- **Genes:** catalase [NCBI Gene 101513499], glutathione S-transferase [NCBI Gene 101256384], 5-enolpyruvyl shikimate-3-phosphate synthase [NCBI Gene 543977], glutathione peroxidase [NCBI Gene 101267098], Catalase [NCBI Gene 543990], Mi-1.2 (root-knot nematode resistance protein) [NCBI Gene 543551], ARF [NCBI Gene 547532], PR-5 (PR-5x) [NCBI Gene 543837], WRKY [NCBI Gene 100127371], JERF3 (GCC box binding protein C.4) [NCBI Gene 543910] {aka Sl-ERF-C-4, SlERF-E3}, Peroxidase [NCBI Gene 543959], APX [NCBI Gene 778224], FESOD (iron superoxide dismutase) [NCBI Gene 544259] {aka Fe-SODle, sodb}, endochitinase [NCBI Gene 101251136], MYB [NCBI Gene 547568], loxD (linoleate 13S-lipoxygenase 3-1, chloroplastic) [NCBI Gene 544009]
- **Diseases:** injury to (MESH:D014947), Meloidogyne incognita infection (MESH:C000656845), citrus greening disease (OMIM:614156), PPNs (MESH:D009349), IPM (MESH:D000081042), SAR (MESH:D063730), death (MESH:D003643), PPN infection (MESH:D007239), toxicity (MESH:D064420), soil-borne diseases (MESH:D005242), M. incognita infection (MESH:C566367), pests (MESH:D029021), necrosis (MESH:D009336), fungal (MESH:D009181), cyst (MESH:D003560)
- **Chemicals:** ABA (MESH:D000040), SA (MESH:D020156), sugar (MESH:D000073893), N (MESH:D009584), ET (MESH:C036216), carbon (MESH:D002244), benzoxazinoids (MESH:D048588), chlorophyll (MESH:D002734), beta-aminobutyric acid (MESH:C047667), Fe (MESH:D007501), ascorbate (MESH:D001205), aldicarb (MESH:D000448), Ascaroside #18 (-), H2O2 (MESH:D006861), ASM (MESH:C099403), K (MESH:D011188), amino acids (MESH:D000596), 2,3-butanediol (MESH:C026978), carbohydrate (MESH:D002241), malondialdehyde (MESH:D008315), Arabic gum (MESH:D006170), callose (MESH:C048306), lipid (MESH:D008055), carbofuran (MESH:D002235), calcium (MESH:D002118), ROS (MESH:D017382), auxin (MESH:D007210), Mg (MESH:D008274), JA (MESH:C011006)
- **Species:** Rhizophagus irregularis (species) [taxon 588596], Beta vulgaris subsp. vulgaris (field beet, subspecies) [taxon 3555], Pseudomonas syringae pv. tomato (no rank) [taxon 323], Meloidogyne graminicola (species) [taxon 189291], Meloidogyne incognita (southern root-knot nematode, species) [taxon 6306], Trichoderma virens (species) [taxon 29875], Pratylenchus penetrans (species) [taxon 45929], Purpureocillium lilacinum (species) [taxon 33203], Bacillus subtilis (species) [taxon 1423], Glycine max (soybean, species) [taxon 3847], Bacillus cereus (species) [taxon 1396], Cicer arietinum (chickpea, species) [taxon 3827], Radopholus similis (banana-root nematode, species) [taxon 46012], Caenorhabditis elegans (species) [taxon 6239], Phoenix dactylifera (date palm, species) [taxon 42345], Meloidogyne javanica (root-knot nematode, species) [taxon 6303], Entrophospora etunicata (species) [taxon 937382], Funneliformis mosseae (species) [taxon 27381], Musa acuminata (banana, species) [taxon 4641], watermelon [taxon 260674], Pseudomonas syringae (species) [taxon 317], Trichoderma harzianum (species) [taxon 5544], Heterodera schachtii (species) [taxon 97005], Ocimum basilicum (basil, species) [taxon 39350], Aphelenchoides besseyi (species) [taxon 269767], Xiphinema index (species) [taxon 46003], Ophiostoma ips (species) [taxon 5163], Meloidogyne hapla (species) [taxon 6305], M. graminicola [taxon 54734], Paenibacillus sp. (species) [taxon 58172], Allium sativum (garlic, species) [taxon 4682], Nicotiana tabacum (American tobacco, species) [taxon 4097], Enterobacterales (order) [taxon 91347], Pasteuria (genus) [taxon 86004], Phacelia tanacetifolia (species) [taxon 94424], Globodera tabacum solanacearum (subspecies) [taxon 65955], Hyaloperonospora arabidopsidis (species) [taxon 272952], Powellomyces sp. EA (species) [taxon 252690], Nematoda (nematode, phylum) [taxon 6231], Ditylenchus dipsaci (species) [taxon 166011], Plasmodium sp. pN (species) [taxon 392219], Arabidopsis thaliana (mouse-ear cress, species) [taxon 3702], Cytobacillus firmus (species) [taxon 1399], Hirschmanniella oryzae (species) [taxon 362338], Steinernema diaprepesi (species) [taxon 193536], Bacteria Latreille et al. 1825 (Bacteria stick insect, genus) [taxon 629395], Pseudomonas jessenii (species) [taxon 77298], Heterodera glycines (soybean cyst nematode, species) [taxon 51029], Bursaphelenchus xylophilus (pine wilt nematode, species) [taxon 6326], Leptographium (genus) [taxon 96312], Serratia ureilytica (species) [taxon 300181], Rotylenchulus reniformis (species) [taxon 239373], Homo sapiens (human, species) [taxon 9606], Pseudomonas synxantha (species) [taxon 47883], Pratylenchus coffeae (species) [taxon 45937], Synechococcus sp. CN (species) [taxon 342326], Cordyceps javanica (species) [taxon 43265], Fusarium oxysporum (species) [taxon 5507], Bacillus thuringiensis (species) [taxon 1428], Solanum tuberosum (potatoes, species) [taxon 4113]

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## References

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Source: https://tomesphere.com/paper/PMC12941151