Host-pathogen interactions are often viewed solely within the context of the evolution and ecology of these two organisms, but non-pathogenic microorganisms associated with a host or vector also mediate pathogen transmission and infection success. This microbiome, made up of pathogenic and non-pathogenic organisms, is therefore integral in understanding host-pathogen dynamics and vector-borne disease ecology. Leveraging natural history collections and field-based systems, I study the interactions between bats, arthropod vectors, and microorganisms using genomics, ecological networks, and machine learning. These host-vector-microbiome interactions provide a model for examining how complex biological communities respond to environmental change and novel disease emergence. Through M-PABI, my future research will continue to build these types of community models, develop collections as One Health resources, and facilitate coordination among institutions, public health professionals, wildlife and pathogen researchers, and communities in zoonotic hot spots. Extending our view of biological communities to include microorganisms is an imperative step towards combating zoonotic events and in maintaining healthy ecosystems. We can harness the information in natural history collections to help us achieve a more holistic approach to spillover prediction and prevention. Hybrid Event - Contact the department for information.