Chronic periodontitis and its keystone pathogen, Porphyromonas gingivalis, have increasingly been linked with Alzheimer's disease (AD). However, P.gingivalis-lipopolysaccharide (LPS) mediated release of neuroinflammatory proteins contributes to AD remains underexplored. In this study, we utilized data-independent acquisition mass spectrometry to characterize P.gingivalis-LPS induced profile of differentially expressed proteins associated with the neuroinflammatory response in human neuroblastoma (SH-SY5Y) and human microglial (HMC3) cells. We reported a set of 124 proteins in SH-SY5Y cells and 96 proteins in HMC3 cells whose levels were significantly upregulated or downregulated by exposure to P. gingivalis-LPS. Our findings demonstrate that P. gingivalis-LPS contributed to the elevated expressions of dementia biomarkers and pro-inflammatory cytokines that include APP, Aβ 1-42 , Aβ 1-40 , T-Tau, p-Tau, VEGF, TGF-β, IL-1β, IL-6 and TNF-α through 2 distinct pathways of extracellular sensing by cell surface receptors and intracellular cytosolic receptors. Interestingly, intracellular signaling proteins activated with P. gingivalis-LPS transfection using Lipofectamine™ 2000 had significantly higher fold change protein expression compared to the extracellular signaling with P. gingivalis-LPS treatment. Additionally, we also explored P. gingivalis-LPS mediated activation of caspase-4 dependent non canonical inflammasome pathway in both SH-SY5Y and HMC3 cells. In summary, P. gingivalis-LPS induced neuroinflammatory protein expression in SH-SY5Y and HMC3 cells, provided insights into the specific inflammatory pathways underlying the potential link between P. gingivalis-LPS infection and the pathogenesis of Alzheimer's disease and related dementias.
Keyphrases
- pi k akt
- cell cycle arrest
- inflammatory response
- lps induced
- cell proliferation
- lipopolysaccharide induced
- induced apoptosis
- anti inflammatory
- endothelial cells
- mass spectrometry
- endoplasmic reticulum stress
- oxidative stress
- cell death
- traumatic brain injury
- risk assessment
- high resolution
- brain injury
- machine learning
- cell surface
- electronic health record