Ecological and Stochastic Determinants of the Growth and Persistence of the Oral Pathogen Porphyromonas gingivalis
Hussein, M.; Barua, A.; Qasaimeh, M.; Smardz, M.; Diaz, P. I.; Hatzikirou, H.
Show abstract
Population density plays a critical role in microbial fitness, yet its influence on pathogen colonization and persistence remains incompletely understood. Porphyromonas gingivalis (Pg) exhibits Allee-type growth, requiring a quorum threshold to replicate, yet is frequently detected at low abundance in vivo. We integrate quantitative growth experiments with mathematical modeling to identify ecological and stochastic determinants of Pg persistence. A cubic Allee-effect model quantifies a quorum threshold below which populations collapse, while conditioned medium from Veillonella parvula (Vp) lowers this threshold, indicating early-colonizer facilitation. Stochastic extensions and Fokker-Planck analysis show that microenvironmental noise enables escapes across the Allee barrier, consistent with long-term subthreshold experiments yielding a stationary, powerlaw-like distribution and under-threshold survival. Pg-Vp co-cultures further demonstrate replicate rescue outcomes for subcritical inocula. Critically, Vp reliably saturates to capacity, constraining terminal phases within the experimental horizon to coexistence (Pg persists with Vp at capacity) or Pg extinction. A two-species replicator model maps these outcomes onto a ({beta}, {gamma}) plane, restricting accessible regions once Vp is established and suggesting interventions that reduce facilitation or variability to restore eubiosis and limit Pg-associated inflammation.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.