Spatial mapping of polymicrobial communities reveals a precise biogeography associated with human dental caries.
Dongyeop KimJuan P BarrazaRodrigo A ArthurAnderson Takeo HaraKarl LewisYuan LiuElizabeth L ScisciEvlambia HajishengallisMarvin WhiteleyHyun KooPublished in: Proceedings of the National Academy of Sciences of the United States of America (2020)
Tooth decay (dental caries) is a widespread human disease caused by microbial biofilms. Streptococcus mutans, a biofilm-former, has been consistently associated with severe childhood caries; however, how this bacterium is spatially organized with other microorganisms in the oral cavity to promote disease remains unknown. Using intact biofilms formed on teeth of toddlers affected by caries, we discovered a unique 3D rotund-shaped architecture composed of multiple species precisely arranged in a corona-like structure with an inner core of S. mutans encompassed by outer layers of other bacteria. This architecture creates localized regions of acidic pH and acute enamel demineralization (caries) in a mixed-species biofilm model on human teeth, suggesting this highly ordered community as the causative agent. Notably, the construction of this architecture was found to be an active process initiated by production of an extracellular scaffold by S. mutans that assembles the corona cell arrangement, encapsulating the pathogen core. In addition, this spatial patterning creates a protective barrier against antimicrobials while increasing bacterial acid fitness associated with the disease-causing state. Our data reveal a precise biogeography in a polymicrobial community associated with human caries that can modulate the pathogen positioning and virulence potential in situ, indicating that micron-scale spatial structure of the microbiome may mediate the function and outcome of host-pathogen interactions.
Keyphrases
- candida albicans
- biofilm formation
- endothelial cells
- pseudomonas aeruginosa
- staphylococcus aureus
- induced pluripotent stem cells
- escherichia coli
- pluripotent stem cells
- healthcare
- oral health
- single cell
- gene expression
- stem cells
- high resolution
- machine learning
- mesenchymal stem cells
- liver failure
- dna methylation
- hepatitis b virus
- deep learning
- cell therapy
- acute respiratory distress syndrome
- mass spectrometry