Pursuing new periodontal pathogens with an improved RNA-oligonucleotide quantification technique (ROQT)

The oral cavity harbors a complex microbiome, with close to 700 predominant taxa demonstrated to be able to colonize the oral cavity (Dewhirst et al., 2010). Most of the current knowledge regarding the microbial aspects of periodontal health and disease as well as results of periodontal treatment are based on the cultivated segment of the microbiome, largely guided by the seminal work of Socransky, Haffajee, Cugini, Smith, and Kent (1998) on the subgingival microbial complexes. However, there is a substantial portion of the oral microbiome that has not yet been fully characterized (15%) or has remained uncultured (35%) (Dewhirst et al., 2010).

Although the role of those organisms in periodontal health and disease is currently unknown, there is no reason to expect that the unrecognized/uncultivated segment of the microbiota harbors fewer pathogens than its cultivated counterpart. In fact, it is possible that a red complex “equivalent” might exist among unrecognized and uncultivated taxa. In that scenario, it becomes crucial to study them in detail, so that their pathogenic properties can be unveiled. However, the first challenge in that process is to determine which organisms are relevant to health maintenance and disease initiation.

As of the writing of this manuscript, there are 107 unrecognized taxa and 203 uncultured phylotypes described in the Human Oral Microbiome Database (www.homd.org, assessed Jan 31, 2023) (Chen et al., 2010). Because it is unlikely that they are all equally important in the pathogenesis of periodontitis, one needs to determine which taxa merit further pursuit in terms of efforts to cultivate and characterize them regarding their metabolism and pathogenicity. Since these are expensive and time consuming endeavors, one needs to determine the prevalence and the levels of those organisms, as only the most commonly detected at a certain numeric abundance are likely to have a role in the dysbiosis that precedes disease initiation. Teles et al. (2011) developed the RNA-Oligonucleotide Quantification Technique, a cost-effective approach to enumerating uncultivated/unrecognized taxa in individual samples of subgingival biofilm samples (Teles et al., 2008, Teles et al., 2011). ROQT can overcome the limitations of other techniques that require sample dilution, sample pooling, or PCR amplification (Amann and Ludwig, 2000, Colombo et al., 2009, de Lillo et al., 2006, Diaz, 2012, Haffajee and Socransky, 2005), all of which can add bias to the microbial results. In addition, it provides quantification, a key piece of information in the study of microbial shifts in periodontal health and disease, as the differences between periodontal health and disease and before and after therapy are quantitative, rather than qualitative (Haffajee et al., 1998, Socransky et al., 1998). The utility of ROQT has been demonstrated in several papers that have helped identify new candidate periodontal pathogens (Gonçalves et al., 2012, Teles et al., 2013, Pérez-Chaparro et al., 2014, Oliveira et al., 2016)

In recent years, our group has been working on several improvements to the technique, with the goal of enhancing its throughput, sensitivity, and specificity. For instance, we have investigated the use of locked nucleic acid (LNA)-modified oligonucleotides probes, which are known to improve the efficiency of hybridization with DNA or RNA targets (Hornyik et al., 2006, Hummelshoj et al., 2005, Kauppinen et al., 2005). We have also evaluated the use of RNA complementary sequences for the preparation of the standards for quantification, instead of the previously used DNA standards. In addition, we have implemented an automated platform for the extraction of Total Nucleic Acids (TNA) from clinical samples by using the King Fisher technology (Bag et al., 2016), which automates the extraction and purification of DNA, RNA, proteins, and cells. KingFisher uses magnetic rods with disposable tip combs to collect beads from solution, then release them into successive wells, each containing reagents for the next step of isolation of the target molecules. This highly effective method of bead collection and transfer leads to clean extractions, efficient results, and preservation of sample. Using a simple process (bind, wash, elute), KingFisher instruments can automate the extraction of DNA and RNA. All these improvements are demonstrated in this manuscript for the first time. Finally, we have capitalized on the increasingly available information from Next-Generation Sequencing (NGS) studies (Keijser et al., 2008, Zaura et al., 2009, Li et al., 2010) to inform the selection of microbial targets of interest. Thus, the purpose of the present study was to optimize the ROQT technique regarding its sensitivity, specificity and cost-effectiveness.

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