Studies | Unique Samples per Visibility Status | Public Samples per Data Type | Users | Jobs |
---|---|---|---|---|
public: 660 private: 167 sandbox: 2,145 submitted to EBI: 711 |
public: 348,213 private: 107,807 sandbox: 438,043 submitted to EBI: 262,725 submitted to EBI (prep): 306,659 |
16S: 321,713 18S: 8,896 ITS: 14,127 Metagenomic: 50,578 Full Length Operon: 803 Metatranscriptomic: 11,764 Metabolomic: 407 Genome Isolate: 1,131 |
10,775 | 576,634 |
Periodontal disease affects the majority of adults worldwide and has been linked to numerous systemic diseases. Despite decades of research, the reasons for the substantial differences among periodontitis patients in disease incidence, progressivity and response to treatment remain poorly understood. While deep sequencing oral bacterial communities has greatly expanded our comprehension of the microbial diversity of periodontal disease and identified associations with healthy and disease states, predicting treatment outcomes remains elusive. Our results suggest that combining multiple ‘omics approaches enhances the ability to differentiate among disease states and determine differential effects of treatment, particularly with the addition of metabolomic information. Furthermore, multi-omics analysis of biofilm community instability indicated these approaches provide new tools for investigating the ecological dynamics underlying the progressive periodontal disease process.