Technology development to explore the relationship between oral health and the oral microbial community

Abstract

The human oral cavity contains a complex microbial community that, until recently, has not been well characterized. Studies using molecular tools have begun to enumerate and quantify the species residing in various niches of the oral cavity; yet, virtually every study has revealed additional new species, and little is known about the structural dynamics of the oral microbial community or how it changes with disease. Current estimates of bacterial diversity in the oral cavity range up to 700 species, although in any single individual this number is much lower. Oral microbes are responsible for common chronic diseases and are suggested to be sentinels of systemic human diseases. Microarrays are now being used to study oral microbiota in a systematic and robust manner. Although this technology is still relatively young, improvements have been made in all aspects of the technology, including advances that provide better discrimination between perfect-match hybridizations from non-specific (and closely-related) hybridizations. This review addresses a core technology using gel-based microarrays and the initial integration of this technology into a single device needed for system-wide studies of complex microbial community structure and for the development of oral diagnostic devices.

Figure 1

Fluorescent image of gel-pad, gel-drop, and waffle arrays. Panel A and B: fluorescent and white-light image of Alexa 594-labeled oligonucleotides hybridized to probes on a subsection of the A) gel-pad array or B) gel-drop array. Panel C: stacked confocal image of Cy3-labeled control probe on a single waffle gel element. Scale bar in Panel A and B is 100 μm and Panel C is 10 μm.

Figure 2

Mean melting profiles of perfect-match and mismatch probes using Alexa 594-labeled rRNA from Streptococcus mutans of six replicates in three experiments. Perfect-match (PM) probe and mismatch (MM) probe have T_d (50% of signal remaining during analysis) values of 41.7°C and 34.0°C, respectively. The 95% confidence intervals are shown as dashed lines and MAX_DCSD is 0.36 and occurs at 40°C. All values were calculated using fANOVA, see text for details (Bugli, submitted).