The gut microbiome, critical to maintaining vertebrate homeostasis, is susceptible to a various exposures. In some cases, these exposures induce dysbiosis, wherein the microbiome changes into a state conducive to disease progression. To better prevent, manage, and treat health disorders, we need to define which exposures induce dysbiosis. Contemporary methods face challenges due to the immense diversity of the exposome and the restricted throughput of conventional experimental tools used for dysbiosis evaluation. We propose integrating high-throughput model systems as an augment to traditional techniques for rapid identification of dysbiosis-inducing agents. Although high-throughput screening tools revolutionized areas such as pharmacology and toxicology, their incorporation in gut microbiome research remains limited. One particularly powerful high-throughput model system is the zebrafish, which affords access to scalable experimentation involving a complex gut microbiome. Numerous studies have employed this model to identify potential dysbiosis triggers. However, its potential could be further harnessed via innovative study designs, such as evaluation of synergistic effects from combined exposures, expansions to the methodological toolkit to discern causal effects of microbiota, and efforts to assess and improve the translational relevance of the model. Ultimately, this burgeoning experimental resource can accelerate the discovery of agents that underlie dysbiotic disorders.