Raffaele, Giulia (2025) Host and symbiont pre-symbiotic interactions: biological investigations towards artificial parallelisms. [Tesi di dottorato]

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Abstract

Soil ecosystems consist of interconnected networks, including mycorrhizal networks (MNs). Mycorrhizal symbiosis is a mutualistic relationship between plant roots and fungi, that evolved to enhance resource acquisition beyond what individual organisms can achieve alone. These networks are essential for carbon cycling and have recently sparked interest for their potential to facilitate inter-plant communication, and function as complex adaptive systems. This thesis explores mycorrhizal symbiosis with a dual objective: advancing the understanding of plant-fungus interactions during the pre-symbiotic phase and identifying parallels between MN characteristics and artificial networks or multi-agent systems. The mycorrhizal symbiosis is known for its peculiar characteristics, such as adaptability, resilience, and resource allocation and management efficiency, which is compelling for artificial networks and robotics. This thesis suggests that MNs can represent a valuable model for developing novel artificial intelligence (AI) models and improving adaptability and robustness in autonomous robots. However, translating biological principles into reliable MN-inspired AI models is challenging due to the complexity of biological systems and the difficulties in data acquisition. This thesis focuses on the pre-symbiotic phase in which the plant undergoes significant morphological and physiological changes in response to mycorrhizal fungi without direct physical contact. This phenomenon exhibits stigmergy-like behavior, where indirect signals trigger plant responses. The experiments involved two model organisms relevant to Agrifood and Environment, the mycorrhizal fungus R. irregularis and the rice plant O. sativa L. The research focused on studying Auxin (IAA), known to regulate root development and lateral root initiation; strigolactones (SLs), which function as key signaling molecules in the pre-symbiotic phase; and nitric oxide (NO), a signaling molecule implicated in root development and biotic interactions. I analyzed the early molecular and morphological responses of rice roots to arbuscular mycorrhizal fungi to investigate these responses, specifically, by analyzing root growth dynamics, hormone signaling (auxin and strigolactones), and nitric oxide production in response to viable and autoclaved spores of R. irregularis. Studying the interplay of phytohormones and signaling molecules involved with these adaptive responses is essential to understanding the regulatory mechanisms underlying the mycorrhizal establishment. Results revealed that the rice root apparatus changes morphologically in the presence of the symbiont. The LLRs grew slower in the presence of mycorrhizal spores and started branching, and density increased, confirming that root proliferation and development are crucial for symbiotic establishment. The roots explore the soil as a collectivity, interact with environmental stimuli, and communicate with neighboring roots, and fungi to optimize nutrient acquisition. Secondly, spore perception induced changes in phytohormone levels. IAA accumulation was observed in both viable and autoclaved spore treatments, correlating with enhanced lateral root elongation, as auxin is a key regulator of lateral root development. Furthermore, NO accumulates in large lateral roots exposed to viable spores, particularly in elongation zones, suggesting a novel regulatory role in modulating root expansion. NO mediates auxin responses in plant growth, suggesting a potential auxin-NO interaction in regulating growth rate and expansion of the root surface area available for symbiosis. Additionally, we found differential trends in canonical and non-canonical SLs, with canonical 4DO decreasing its content and Oro increasing, because of their involvement in the root growth. From a biological perspective, this study sheds light on the signaling mechanisms underlying early mycorrhizal perception in rice, revealing potential crosstalk between auxin, SLs and NO that modulate root architecture. By elucidating these interactions, this research also informs sustainable agricultural practices and gives ideas for bio-based strategies to improve crop performance and plant resilience. Such applications align with the “Sustainable Development Goals” (SDGs), particularly Goal 2, which seeks to promote sustainable agriculture and food security, and Goal 13, which addresses climate change mitigation and adaptation. From an engineering perspective, these findings could suggest new communication strategies for artificial systems. By integrating principles derived from root tropism and growth plasticity, this study lays the groundwork for bioinspired algorithms that could enhance efficiency and adaptability in artificial systems. These characteristics are fundamental for an ecological system and thus have the potential to inspire swarm intelligence.

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