Changes in oral microbial profiles after peridontal treatment as determined by molecular analysis of 16S rRNA genes.

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pdfSakamoto M, Huang Y, Ohnishi M, Umeda M, Ishikawa I & Benno Y. 2004 Changes in oral microbial profiles after peridontal treatment as determined by molecular analysis of 16S rRNA genes. J. Med. Microbiol. 53:563-571.

Question: How does the peridontal microflora change after treatment?.

In this paper, the authors use t-RFLP to study subgingival plaque of 3 peridontal disease patients before and after treatment (lessons in oral hygiene and very complete teeth cleaning ("scaling and planing") both above and below the gums). Samples were taken from the subgingiva of 3 or 4 teeth before treatment and 3 months after treatment.

Although the authors use realtime PCR and ssu-rDNA clone libraries as well as t-RFLP, let's go through the t-RFLP data first.

t-RFLP was started by PCR amplification from the samples using 6-FAM-labeled 27F (bacterial-specific) and 1492R (universal). Samples of the PCR products were digested with HhaI (GCG^C) and MspI (C^CGG), and run on a sequencing machine.

Fig 1 is an example of their data from the HhaI digests:


The code is that the first letter represents the patient (A, B or C), the second represents whether the sample was plaque (P) or saliva (S), and the number is before (1) or after (2) treatment. At this point, these are viewed as fingerprints; the identities of the organisms represented by the peaks are not important. What shows up is that there are differences before & after treatment. These are pretty subtle for patient A, but clear in the cases of patients B and C.

Fig 3 is a better example of how the data is examined. The top panel (a) are the HhaI digests from one site on one patient, before (top) and after (bottom) treatment. The bottom panel (b) is the same thing with the MspI digest. Notice that after treatment (this is patient B), the Peptostreptococcus, Porphyromonas ginginvalis, and Prevotella intermedia (know problem organisms) all disappear or diminish. The other organisms, which are creatures that the authors showed using these same methods are common in healthly individuals, remain abundant.

Given that t-RFLP is new technology, they used realtime PCR and more traditional ssu-rDNA clone libraries to confirm the results of their t-RFLP. They discuss these at some length in the paper, but we'll keep it brief. First they use realtime PCR with species-specific primers to determine to numbers of cells of several species in each sample:


Notice that they're looking specifically for some common oral spirochaetes. Notice also that although patient A didn't have much change in these problem organisms, patients B and C had dramatic decreases in them all. However, notice as well that these particular organisms (the spirochaetes) did not show up in their t-RFLP experiments; this is probably why they did these realtime PCRs.

They also cloned sequences from their PCRs, and counted species found before & after treatment:


So this is the traditional ssu-rRNA microbial survey method. They look at a relatively small number of clones, 90 before and 88 after treatment in a single tooth of a single patient, but it looks even here like you can see pathogens decreasing or disappearing, being replaced by commensals. However, given the small numbers (rarely more than a handful of any one organism), this table really should have included some statistics to show whether or not these are significant.

The take-home message is that these confirm the observations of the t-RFLP; known harmful organisms are reduced and commensalistic ones remain constant or increase, long-term after peridontal treatment.