Worlds Apart – Transcriptome Profiles of Key Oral Microbes in the Periodontal Pocket Compared to Single Laboratory Culture Reflect Synergistic Interactions

Periodontitis is a worldwide prevalent oral disease which results from dysbiosis of the periodontal microbiome. Some of the most active microbial players, e.g. Porphyromonas gingivalis, Treponema denticola and Fusobacterium nucleatum, have extensively been studied in the laboratory, but it is unclear to which extend these findings can be transferred to in vivo conditions. Here we show that the transcriptional profiles of P. gingivalis, T. denticola and F. nucleatum in the periodontal niche are distinct from those in single laboratory culture and exhibit functional similarities. GO (gene ontology) term enrichment analysis showed up-regulation of transporters, pathogenicity related traits and hemin/heme uptake mechanisms for all three species in vivo. Differential gene expression analysis revealed that cysteine proteases, transporters and hemin/heme-binding proteins were highly up-regulated in the periodontal niche, while in these species. Unexpectedly, a number of genes involved in DNA modification such as genes encoding CRISPR-Cas, restriction-modification enzymes, transposases, integrases and helicases were considerably down-regulated. in periodontal pocket. The data suggest strong interactions between those three species regarding protein degradation, iron up-take, and mobility in vivo, explaining their enhanced synergistic pathogenicity. We discovered A striking difference between in vivo conditions and laboratory culture was the a strikingly high frequency of Single Nucleotide Polymorphisms (SNPs) in vivo. For F. nucleatum we discovered a total of 127,729 SNPs in periodontal niche transcripts, while only 35 were found in laboratory culture transcripts. The SNPs which were found in similar frequency in health and disease and covered the entire genome, suggesting continuous evolution in the host. We conclude that metabolic interactions shape gene expression in vivo. that gGreat caution is required when inferring in vivo metabolism and pathogenicity of microbes from laboratory data, and that microdiversity is an important adaptive trait of natural communities.