Identification of pathogen and host-response markers correlated with periodontal disease

BACKGROUND: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm. METHODS: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers. RESULTS: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5). CONCLUSIONS: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.

Soil property and management effects on grassland microbial communities across a latitudinal gradient in Germany

There is much interest in the identification of the main drivers controlling changes in the microbial community that may be related to sustainable land use. We examined the influence of soil properties and land-use intensity (N fertilization, mowing, grazing) on total phospholipid fatty acid (PLFA) biomass, microbial community composition (PLFA profiles) and activities of enzymes involved in the C, N, and P cycle. These relationships were examined in the topsoil of grasslands from three German regions (Schorfheide-Chorin (SCH), Hainich-Dun (HAI), Schwabische Alb (ALB)) with different parent material. Differences in soil properties explained 60% of variation in PLFA data and 81% of variation in enzyme activities across regions and land-use intensities. Degraded peat soils in the lowland areas of the SCH with high organic carbon (OC) concentrations and sand content contained lower PLFA biomass, lower concentrations of bacterial, fungal, and arbuscular mycorrhizal PLFAs, but greater enzyme activities, and specific enzyme activities (per unit microbial biomass) than mineral soils in the upland areas of the HAI and ALB, which are finer textured, drier, and have smaller OC concentrations. After extraction of variation that originated from large-scale differences among regions and differences in land-use intensities between plots, soil properties still explained a significant amount of variation in PLFA data (34%) and enzyme activities (60%). Total PLFA biomass and all enzyme activities were mainly related to OC concentration, while relative abundance of fungi and fungal to bacterial ratio were mainly related to soil moisture. Land-use intensity (LUI) significantly decreased the soil C:N ratio. There was no direct effect of LUI on total PLFA biomass, microbial community composition, N and P cycling enzyme activities independent of study region and soil properties. In contrast, the activities and specific activities of enzymes involved in the C cycle increased significantly with LUI independent of study region and soil properties, which can have impact on soil organic matter decomposition and nutrient cycling. Our findings demonstrate that microbial biomass and community composition as well as enzyme activities are more controlled by soil properties than by grassland management at the regional scale. (C) 2013 Elsevier B.V: All rights reserved.