Characterization of Microbiome-Mediated

Immunity From Mimicry to Microproteins: Mining the Human Microbiome for Next-Generation Immunotherapies

The gut microbiome has co-evolved with its host to shape innate and adaptive immunity through antigen presentation and metabolite signaling. Molecular mimicry is an underappreciated mechanism within this relationship: commensal bacteria expressing antigens
similar to tumor-associated or pathogen epitopes can generate memory T and B cells that crossreact with disease targets, a “natural immunization” effect documented across anticancer immunosurveillance, vaccine response modulation, and autoimmunity. Modern AI tools, including deep learning and large language models applied to multi-omics data, now make it feasible to characterize these interactions at unprecedented scale and to integrate metagenomic, proteomic, and metabolomic signals into predictive models of immune outcome. Within this framework, one research axis focuses on established mimicry biology to identify microbial features associated with beneficial immune priming or pathological cross-reactivity, while a second axis explores whether de novo gene emergence and microprotein evolution provide a new source of immunomodulatory molecules under the selective pressures imposed by Western diets and antibiotic exposure. Functional screening in Drosophila melanogaster gnotobiotic models enables rapid testing of candidate microbes and molecular effectors in a controlled host context, and prioritized candidates can then be advanced to more complex validation systems and used to inform the development of CRISPR-engineered commensal therapeutics. Acute myeloid leukemia can serve as an initial proof-of-concept indication for translational development. Overall, this framework connects microbiome evolution, immune modulation, and synthetic biology into a single path for discovering next-generation microbiome-based interventions for cancer and infectious diseases.

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