Abstract
Microbial interactions dictate the structure and function of microbiomes, but the complexity of natural communities can obscure the individual interactions. Model microbial communities constructed with genetically tractable strains known to interact in natural settings can untangle these networks and reveal underpinning mechanisms. Our model system, The Hitchhikers of the Rhizosphere (THOR), is composed of three species-Bacillus cereus, Flavobacterium johnsoniae, and Pseudomonas koreensis-that co-isolate from field-grown soybean roots. Comparative metatranscriptomics on THOR revealed global patterns of interspecies transcriptional regulation. When grown in pairs, each member of THOR exhibits unique signaling behavior. In the community setting, gene expression is dominated by pairwise interactions with Pseudomonas koreensis mediated either directly or indirectly by its production of the antibiotic koreenceine-the apparent "hammer" of THOR. In pairwise interactions, the koreenceine biosynthetic cluster is responsible for 85 and 22% of differentially regulated genes in F. johnsoniae and B. cereus, respectively. Although both deletion of the koreenceine locus and reduction of P. koreensis inoculum size increase F. johnsoniae populations, the transcriptional response of P. koreensis is only activated when it is a relative minority member at the beginning of coculture. The largest group of upregulated P. koreensis genes in response to F. johnsoniae are those without functional annotation, indicating that focusing on genes important for community interactions may offer a path toward functional assignments for unannotated genes. This study illustrates the power of comparative metatranscriptomics of microorganisms encountering increasing microbial complexity for understanding community signal integration, antibiotic responses, and interspecies communication. IMPORTANCE The diversity, ubiquity, and significance of microbial communities is clear. However, the predictable and reliable manipulation of microbiomes to impact human, environmental, and agricultural health remains a challenge. Effective remodeling of microbiomes will be enabled by understanding the interspecies interactions that govern community processes. The extreme complexity of most microbiomes has impeded characterization of the relevant interactions. Investigating the genetics and biochemistry of simplified, model microbiomes could unearth specific interactions and generate predictions about community-governing principles. Here, we use one such model community to quantify changes in gene expression of individual species as they encounter stimuli from one or more species, directly mapping combinatorial interspecies interactions. A surprising amount of gene expression is regulated by a single molecule, the antibiotic koreenceine, which appears to impact gene regulation across community networks.