2.6.1 Pipelines and softwares
There are basically two different approaches for data-analysis: a clustering-first approach, such as mothur, QIIME and BMP, and an assignment-first approach, such as Kraken, CLARK, One Codex, (Siegwald et al., 2017) and DADA2 (Callahan et al., 2016). The OCToPUS (Optimized CATCh, mothur, IPED, UPARSE, and SPAdes) pipeline was developed to utilize the benefits of various tools and state-of-the-art algorithms (Mysara et al., 2017; T. Kim et al., 2018), but no comparative studies have yet been made. Depending on the pipeline, the data analysis protocols differ. First, the quality of the sequences is screened and poor-quality bases are removed. After a quality check, primers should be removed before merging the sequences into contigs.
Chimera and contaminants are filtered before assigning taxonomy with or without grouping the contigs into operative taxonomic units (OTUs) (Kozich et al., 2013;
Callahan et al., 2016).
Mothur
Mothur was introduced in 2009 by Patrick Schloss, aiming to be a comprehensive software package allowing users to use a single software package to analyze community sequence data. Mothur builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data (Schloss et al., 2009).
The amplicon sequencing approach using mothur can also be highly suitable for rapid detection and identification of viruses of interest in complex water matrices (Ogorzaly et al., 2015). As well as for other common softwares, there is is standard operational protocol for mothur (Kozich et al., 2013).
QIIME
QIIME was introduced in 2010 by Caporaso and colleagues (Caporaso et al., 2010). It provides a wide range of microbial community analyses and visualizations, as well as graphical displays allowing users to interact with the data (Caporaso et al., 2010).
There is a standard operational protocol for basic analyses and creating basic graphs using QIIME, which also provides clear instructions for installation of the software (Kuczynski et al., 2012). If the SILVA database is used, both QIIME and mothur produce comparable richness and diversity results (López-García et al., 2018).
DADA2
DADA2 is an R-package (R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL:
https://www.R-project.org/) that models and corrects Illumina-sequenced amplicon errors. By comparison to Mothur and qiime, DADA2 algorithm is based on a different idea: DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. DADA2 is well suitable for Illumina data. (Callahan et al., 2016) Nowadays DADA2 is also suitable for 454 and IonTorrent data, but some changes must be made for the parameters as described in the DADA2 pipeline tutorial (https://benjjneb.github.io/dada2/tutorial.html). Since coarse-graining into OTUs may cause distortion of the data, there is increasing interest in the DADA2 algorithm (Kopylova et al., 2016; Edgar, 2017), which in one recent study resulted in the most accurate predictions of the mock community phylogeny, taxonomy, and diversity with the Greengenes database (Xue, Kable and Marco, 2018).
2.6 TOOLS FOR DATA ANALYSIS
2.6.1 Pipelines and softwares
There are basically two different approaches for data-analysis: a clustering-first approach, such as mothur, QIIME and BMP, and an assignment-first approach, such as Kraken, CLARK, One Codex, (Siegwald et al., 2017) and DADA2 (Callahan et al., 2016). The OCToPUS (Optimized CATCh, mothur, IPED, UPARSE, and SPAdes) pipeline was developed to utilize the benefits of various tools and state-of-the-art algorithms (Mysara et al., 2017; T. Kim et al., 2018), but no comparative studies have yet been made. Depending on the pipeline, the data analysis protocols differ. First, the quality of the sequences is screened and poor-quality bases are removed. After a quality check, primers should be removed before merging the sequences into contigs.
Chimera and contaminants are filtered before assigning taxonomy with or without grouping the contigs into operative taxonomic units (OTUs) (Kozich et al., 2013;
Callahan et al., 2016).
Mothur
Mothur was introduced in 2009 by Patrick Schloss, aiming to be a comprehensive software package allowing users to use a single software package to analyze community sequence data. Mothur builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data (Schloss et al., 2009).
The amplicon sequencing approach using mothur can also be highly suitable for rapid detection and identification of viruses of interest in complex water matrices (Ogorzaly et al., 2015). As well as for other common softwares, there is is standard operational protocol for mothur (Kozich et al., 2013).
QIIME
QIIME was introduced in 2010 by Caporaso and colleagues (Caporaso et al., 2010). It provides a wide range of microbial community analyses and visualizations, as well as graphical displays allowing users to interact with the data (Caporaso et al., 2010).
There is a standard operational protocol for basic analyses and creating basic graphs using QIIME, which also provides clear instructions for installation of the software (Kuczynski et al., 2012). If the SILVA database is used, both QIIME and mothur produce comparable richness and diversity results (López-García et al., 2018).
DADA2
DADA2 is an R-package (R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL:
https://www.R-project.org/) that models and corrects Illumina-sequenced amplicon errors. By comparison to Mothur and qiime, DADA2 algorithm is based on a different idea: DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. DADA2 is well suitable for Illumina data. (Callahan et al., 2016) Nowadays DADA2 is also suitable for 454 and IonTorrent data, but some changes must be made for the parameters as described in the DADA2 pipeline tutorial (https://benjjneb.github.io/dada2/tutorial.html). Since coarse-graining into OTUs may cause distortion of the data, there is increasing interest in the DADA2 algorithm (Kopylova et al., 2016; Edgar, 2017), which in one recent study resulted in the most accurate predictions of the mock community phylogeny, taxonomy, and diversity with the Greengenes database (Xue, Kable and Marco, 2018).
3 AIMS OF THE STUDY
The aim of this study was to assess the possible role of dental and periodontal infections in pathogenesis of intracranial aneurysm disease. The specific aims were to assess:
1. The presence of oral and pharyngeal bacterial DNA in ruptured and unruptured intracranial aneurysms (Studies I, II).
2. The bacterial communities of gingival crevicular fluid in patients subjected to preoperative dental examination before surgical treatment of saccular intracranial aneurysm, using qPCR and 16S rRNA gene-based metagenomic analyses (Studies III, IV).
3. The possible presence of dental infectious foci in patients undergoing preoperative dental examination before surgical treatment of saccular intracranial aneurysm (Study III).
4. The association between tooth brushing frequency and bacterial communities in patients subjected to preoperative dental examination before surgical treatment of saccular intracranial aneurysm (Study IV).
3 AIMS OF THE STUDY
The aim of this study was to assess the possible role of dental and periodontal infections in pathogenesis of intracranial aneurysm disease. The specific aims were to assess:
1. The presence of oral and pharyngeal bacterial DNA in ruptured and unruptured intracranial aneurysms (Studies I, II).
2. The bacterial communities of gingival crevicular fluid in patients subjected to preoperative dental examination before surgical treatment of saccular intracranial aneurysm, using qPCR and 16S rRNA gene-based metagenomic analyses (Studies III, IV).
3. The possible presence of dental infectious foci in patients undergoing preoperative dental examination before surgical treatment of saccular intracranial aneurysm (Study III).
4. The association between tooth brushing frequency and bacterial communities in patients subjected to preoperative dental examination before surgical treatment of saccular intracranial aneurysm (Study IV).