Data_Sheet_1_Microbial signatures in human periodontal disease: a metatranscriptome meta-analysis.zip

The characterization of oral microbial communities and their functional potential has been shaped by metagenomics and metatranscriptomics studies. Here, a meta-analysis of four geographically and technically diverse oral shotgun metatranscriptomics studies of human periodontitis was performed. In total, 54 subgingival plaque samples, 27 healthy and 27 periodontitis, were analyzed. The core microbiota of the healthy and periodontitis group encompassed 40 and 80 species, respectively, with 38 species being common to both microbiota. The differential abundance analysis identified 23 genera and 26 species, that were more abundant in periodontitis. Our results not only validated previously reported genera and species associated with periodontitis with heightened statistical significance, but also elucidated additional genera and species that were overlooked in the individual studies. Functional analysis revealed a significant up-regulation in the transcription of 50 gene families (UniRef-90) associated with transmembrane transport and secretion, amino acid metabolism, surface protein and flagella synthesis, energy metabolism, and DNA supercoiling in periodontitis samples. Notably, the overwhelming majority of the identified gene families did not exhibit differential abundance when examined across individual datasets. Additionally, 4 bacterial virulence factor genes, including TonB dependent receptor from P. gingivalis, surface antigen BspA from T. forsynthia, and adhesin A (PsaA) and Type I glyceraldehyde-3-phosphate dehydrogenase (GAPDH) from the Streptococcus genus, were also found to be significantly more transcribed in periodontitis group. Microbial co-occurrence analysis demonstrated that the periodontitis microbial network was less dense compared to the healthy network, but it contained more positive correlations between the species. Furthermore, there were discernible disparities in the patterns of interconnections between the species in the two networks, denoting the rewiring of the whole microbial network during the transition to the disease state. In summary, our meta-analysis has provided robust insights into the oral active microbiome and transcriptome in both health and disease.