show Abstracthide AbstractStrategies that promote functional organ growth with minimal adverse effects are the ultimate goal of regenerative medicine but no single approach is currently available for organ level repair. Here, using an evolutionary adapted in vivo infection model - Mycobacterium leprae, with host cell reprogramming ability and its natural animal host, the nine-banded armadillo (Dasypus novemcinctus) that harbor bacteria in the highly regenerative liver - we present an in vivo model for promoting adult liver growth at organ level without adverse effects. Experimentally infected armadillos harboring bacteria in the liver, but not infection-resistant or drug-treated animals, showed a significantly increased total liver: body weight ratio, indicative of bacterial-driven liver organ growth in living animals. The machine-learning approach revealed an increase in healthy liver lobule number with a proportionate expansion of the hepatocyte mass with integrating vasculature and biliary networks responsible for functional liver growth. Intriguingly, infected enlarged livers show intact microarchitecture but without evidence of hepatocellular damage, fibrosis/scarring or tumorigenesis. Reactivation of armadillo liver progenitor and developmental genes/proteins, as well as upregulation of growth-, metabolism- and differentiation-associated markers with minimal change in oncogenes or tumor suppressor genes, suggests that bacteria have adapted dynamic regenerative, homeostasis and reprogramming mechanisms to promote de novo organogenesis while maintaining tissue integrity and tumor preventive strategies for host-dependent bacterial propagation. Thus, our model may facilitate the unravelling of in vivo endogenous regenerative pathways that effectively re-engage liver organ growth, with broad implications. Overall design: Triplicate RNA samples isolated from 24-month ML-infected, 30-month ML-infected and two control Armadillo livers were collected and used for paired-end sequencing. This was used for differential gene expression analysis between infected and control samples.