Holo-omic applications to unveil microbiome shaping sustainable horticultural production

Abstract

Plant-associated microorganisms play a key role in the future sustainability of terrestrial ecosystems. In nature, plants and their associated microbiome can form an assemblage of species, considered interacting metaorganisms or holobionts. Horticultural plants, including vegetables, fruit and berries, and ornamentals live in intimate association with complex and diverse microbial communities that have evolved a myriad of cooperative and competitive interaction mechanisms that shape the holobiont fitness. Nonetheless, our understanding of these interactions in shaping more complex microbial horticulture communities, along with their relevance for host growth, fitness, stress resilience, and health in a more natural context remains sparse. In this perspective, the holo-omic landscape that requires careful consideration of study design and integrates multi-omic data from both host and microbiota domains is a promising approach to unveil the interplay between the two to advance horticultural production. The analysis of horticulture (meta)-omics and phenotyping, along with mechanistic experiments in model systems, is revolutionizing research by enhancing our ability to understand the structure and core function of the plant-associated microbiome. These advancements are complemented by improvements in the throughput and accuracy of DNA sequencing, enabling us to delve deeper into the genomes of microbial communities. Yet, many challenges remain. We focus this review on the potential for holo-omics to generate a more holistic perspective of molecular networks, and we further discuss the implementation and current limitations of the holo-omic approach within microbial horticulture. We argue that holo-omics will pave the way to improve, from a horticultural perspective, food security and safety, sustainability, breeding practices, development of microbiota- and host-tailored horticultural crops’ health treatments and increasing production efficiency.