Understanding the consequences of microbe-microbe interactions is critical in efforts to predict the function of microbiomes and to manipulate or construct communities to achieve desired outcomes. The investigation of these interactions poses a significant challenge -in part due to the lack of suitable experimental tools. We present the Microwell Recovery Array, a high throughput approach designed to rapidly screen interactions across a microbiome and uncover higher-order combinations of strains that either inhibit or promote the function of a GFP-producing focal species. One experiment generates 10 4 unique microbial communities that contain a focal species combined with a unique combination of previously uncharacterized cells from plant rhizosphere. Cells are then sequentially extracted from individual co-culture wells that display highest or lowest levels of focal species function using a novel high-resolution photopolymer extraction system. Microbes present are subsequently identified and the putative interactions are validated. Using this approach, we screen the Populus trichocarpa rhizosphere for bacterial strains affecting the survival and growth of Pantoea sp. YR343, a plant growth promoting strain isolated from the P. trichocarpa rhizosphere. We were able to simultaneously isolate and validate multiple Stenotrophomonas strains that antagonize strain YR343 growth and a set of Enterobacter strains that promote strain YR343 growth. The latter demonstrates the unique ability of the platform to uncover multimembered consortia that generate emergent phenotypes. This knowledge will inform the development of beneficial consortia that promote the production of Populus biofuel feedstock, while the platform is adaptable to screening higher-order interactions in any microbiome of interest. Significance StatementAchieving a fundamental understanding of microbe-microbe interactions that occur within microbial communities is a grand challenge in microbiology due to the limited experimental tools available. In this report, we describe a new tool that enables one to screen microbial interactions across thousands of compositionally unique communities to discover collections of bacteria that antagonize or promote the survival and growth of bacteria with important functions. This approach has the unique ability to uncover higher-order combinations of bacteria that generate emergent

Understanding microbe-microbe interactions is critical to predict microbiome function and to construct communities for desired outcomes. Investigation of these interactions poses a significant challenge due to the lack of suitable experimental tools available. Here we present the microwell recovery array (MRA), a new technology platform that screens interactions across a microbiome to uncover higher-order strain combinations that inhibit or promote the function of a focal species. One experimental trial generates 104 microbial communities that contain the focal species and a distinct random sample of uncharacterized cells from plant rhizosphere. Cells are sequentially recovered from individual wells that display highest or lowest levels of focal species growth using a high-resolution photopolymer extraction system. Interacting species are then identified and putative interactions are validated. Using this approach, we screen the poplar rhizosphere for strains affecting the growth of Pantoea sp. YR343, a plant growth promoting bacteria isolated from Populus deltoides rhizosphere. In one screen, we montiored 3,600 microwells within the array to uncover multiple antagonistic Stenotrophomonas strains and a set of Enterobacter strains that promoted YR343 growth. The later demonstrates the unique ability of the platform to discover multi-membered consortia that generate emergent outcomes, thereby expanding the range of phenotypes that can be characterized from microbiomes. This knowledge will aid in the development of consortia for Populus production, while the platform offers a new approach for screening and discovery of microbial interactions, applicable to any microbiome.