How conserved are the conserved 16S-rRNA regions?

Abstract

The 16S rRNA gene has been used as master key for studying prokaryotic diversity in almost every environment. Despite the claim of several researchers to have the best universal primers, the reality is that no primer has been demonstrated to be truly universal. This suggests that conserved regions of the gene may not be as conserved as expected. The aim of this study was to evaluate the conservation degree of the so-called conserved regions flanking the hypervariable regions of the 16S rRNA gene. Data contained in SILVA database (release 123) were used for the study. Primers reported as matches of each conserved region were assembled to form contigs; sequences sizing 12 nucleotides (12-mers) were extracted from these contigs and searched into the entire set of SILVA sequences. Frequency analysis shown that extreme regions, 1 and 10, registered the lowest frequencies. 12-mer frequencies revealed segments of contigs that were not as conserved as expected (≤90%). Fragments corresponding to the primer contigs 3, 4, 5b and 6a were recovered from all sequences in SILVA database. Nucleotide frequency analysis in each consensus demonstrated that only a small fraction of these so-called conserved regions is truly conserved in non-redundant sequences. It could be concluded that conserved regions of the 16S rRNA gene exhibit considerable variation that has to be considered when using this gene as biomarker.

Size-variable zone in V3 region of 16S rRNA

“…These regions are also called hypervariable regions and have been used as differentiators; however, recent evidence has demonstrated that conserved regions may also exhibit some degree of variation, thus potentially introducing bias. 5,6 Differences in 16S gene size have been detected in different bacteria species, ranging from »1200 to 1500 nucleotides; this can also be confirmed by database sequence mining. However, it is difficult to obtain larger fractions of partial sequences because the primers used for in silico tests are not universal.…”

“…The distance between conserved regions was calculated using a 12-mers technique, based on the algorithm reported by Mart ınez-Porchas et al 5 In short, primers that had been reported as matches of each conserved region were assembled to form contigs; sequences of 12 nucleotides (12-mers) were extracted from these contigs and used to search the entire set of SILVA sequences. If a 12-mer contained degenerations, each isoform was considered for analysis.…”

“…Recently, a method using k-mers that allows the determination of the most conserved regions of each rRNA region has been described. 5 Taking advantage of this method, most of the reported sequences, either partial or complete, could be linked from robust databases and grouped to be studied. Several reports have described the compensatory mutation process of RNA helices as the main factor contributing to variability in the 16S gene sequence, with AU and UA pairs [7][8][9] and single insertions and deletions (indel) as the major factors influencing size.…”

Tracing insect pests: is there new potential in molecular techniques?

“…There are ten of these conserved regions, all of which have been annotated. Between these conserved regions exist so-called 'hypervariable' regions whose sequence is not 'essential' to the ribosomal conformation (Martinez-Porchas et al, 2017). There are nine of these hypervariable regions, annotated from V1 to V9 (Fig.…”

Comparison of two bioinformatics tools used to characterize the microbial diversity and predictive functional attributes of microbial mats from Lake Obersee, Antarctica

“…Traditionally, NGS technology has targeted bacterial 16S rRNA genes (V1–V9 segments) within metacommunity DNA revealing the taxonomic diversity of microbial communities in ecosystems of interest at the highest possible coverage (Chakravorty et al, 2007; Huse et al, 2008; Martinez-Porchas et al, 2017; Sanschagrin and Yergeau, 2014; Shah et al, 2011). Powerful bioinformatics tools such as PICRUSt, Tax4Fun, and Piphillin have been recently introduced that utilize 16S rRNA gene-based taxonomic information to predict the functional attributes of microbial assemblages (Aßhauer et al, 2015; Iwai et al, 2016; Langille et al, 2013).…”