Periodontal disease (PD) develops from a synergy of complex subgingival oral microbiome, and is linked to systemic inflammatory atherosclerotic vascular disease (ASVD). To investigate how a polybacterial microbiome infection influences atherosclerotic plaque progression, we infected the oral cavity of ApoE null mice with a polybacterial consortium of 4 well-characterized periodontal pathogens, Porphyromonas gingivalis, Treponema denticola, Tannerealla forsythia and Fusobacterium nucleatum, that have been identified in human atherosclerotic plaque by DNA screening. We assessed periodontal disease characteristics, hematogenous dissemination of bacteria, peripheral T cell response, serum inflammatory cytokines, atherosclerosis risk factors, atherosclerotic plaque development, and alteration of aortic gene expression. Polybacterial infections have established gingival colonization in ApoE null hyperlipidemic mice and displayed invasive characteristics with hematogenous dissemination into cardiovascular tissues such as the heart and aorta. Polybacterial infection induced significantly higher levels of serum risk factors oxidized LDL (p < 0.05), nitric oxide (p < 0.01), altered lipid profiles (cholesterol, triglycerides, Chylomicrons, VLDL) (p < 0.05) as well as accelerated aortic plaque formation in ApoE null mice (p < 0.05). Periodontal microbiome infection is associated with significant decreases in Apoa1, Apob, Birc3, Fga, FgB genes that are associated with atherosclerosis. Periodontal infection for 12 weeks had modified levels of inflammatory molecules, with decreased Fas ligand, IL-13, SDF-1 and increased chemokine RANTES. In contrast, 24 weeks of infection induced new changes in other inflammatory molecules with reduced KC, MCSF, enhancing GM-CSF, IFNγ, IL-1β, IL-13, IL-4, IL-13, lymphotactin, RANTES, and also an increase in select inflammatory molecules. This study demonstrates unique differences in the host immune response to a polybacterial periodontal infection with atherosclerotic lesion progression in a mouse model.