Synthetic microbial communities: a systems approach to understanding root microbiome dynamics and functioning

When plants grow in soil, their roots release carbon molecules that attract microbes. These microbes colonize the roots and form a complex system known as the root microbiome. Similar to the human gut microbiome, a balanced and diverse root microbiome offers numerous benefits to its host. For plants, these benefits include enhanced immunity, suppression of pathogens, improved nutrient uptake, and greater tolerance to environmental stresses. To harness these beneficial interactions and make crops more resilient, it is crucial to understand how the root microbiome is established and how it functions as beneficial microbial activities, such as pathogen suppression, depend on the microbes successfully establishing themselves in the root microbiome. To study this, I conducted synthetic community (SynCom) inoculation experiments. SynComs are communities of microbes that were originally extracted from plant roots when grown in natural soil. In SynCom experiments, these microbes are recultivated and mixed into controlled microbial communities, which are subsequently introduced to plants in sterile conditions to examine how microbes interact with each other and interact with the plant to form root communities. In my thesis, I analyzed both experimental and publicly available SynCom datasets to explore root microbiome assembly and functioning. First, I discuss the challenges of root microbiome research and how SynCom experiments help overcome these challenges (Chapter 1). In Chapter 2, I uncover key principles of root microbiome assembly, including how plants prioritize bacterial functions over genera, how the selection of bacterial functions occurs at the family level, how hosts exhibit unique patterns in selecting bacterial functions, and how functionally diverse bacteria are more likely to successfully colonize roots. In Chapter 3, a metagenome-wide association study highlights that key traits, such as the ability to metabolize diverse compounds, motility, immune evasion strategies, and the capacity to inhibit other microbes, are crucial for competitive bacterial colonization of plant roots. In Chapter 4, I developed a tool to identify and quantify SynCom isolates in complex SynCom datasets, achieving better performance than existing benchmark tools. In Chapter 5, I analyze publicly available SynCom datasets and reveal that microbial communities often exist in distinct functional states, influenced by the presence or absence of Bacillus bacteria, highlighting the ecological importance of this species in the root microbiome. Finally, in Chapter 6, I discuss the role of artificial intelligence and machine learning in modeling the root microbiome, how the experimental findings in the other chapters contribute to this effort, and the challenges involved in building predictive models for the complex interactions within the root microbiome. Conclusively, I demonstrate in this thesis how combining complex SynCom experiments with advanced bioinformatics can unravel the complexities of the root microbiome. My findings identify key principles of root microbiome assembly and the essential microbial functions required for root colonization. In the long term, this research may help develop bioinoculants by designing microbial consortia that enhance the effective establishment of bioinoculants in the root microbiome. This, in turn, could improve crop resilience to stresses, addressing challenges intensified by climate change.