Critical review of 16S rRNA gene sequencing workflow in microbiome studies: From primer selection to advanced data analysis

Abstract

The multi‐batch reanalysis approach of jointly reevaluating gene/genome sequences from different works has gained particular relevance in the literature in recent years. The large amount of 16S ribosomal ribonucleic acid (rRNA) gene sequence data stored in public repositories and information in taxonomic databases of the same gene far exceeds that related to complete genomes. This review is intended to guide researchers new to studying microbiota, particularly the oral microbiota, using 16S rRNA gene sequencing and those who want to expand and update their knowledge to optimise their decision‐making and improve their research results. First, we describe the advantages and disadvantages of using the 16S rRNA gene as a phylogenetic marker and the latest findings on the impact of primer pair selection on diversity and taxonomic assignment outcomes in oral microbiome studies. Strategies for primer selection based on these results are introduced. Second, we identified the key factors to consider in selecting the sequencing technology and platform. The process and particularities of the main steps for processing 16S rRNA gene‐derived data are described in detail to enable researchers to choose the most appropriate bioinformatics pipeline and analysis methods based on the available evidence. We then produce an overview of the different types of advanced analyses, both the most widely used in the literature and the most recent approaches. Several indices, metrics and software for studying microbial communities are included, highlighting their advantages and disadvantages. Considering the principles of clinical metagenomics, we conclude that future research should focus on rigorous analytical approaches, such as developing predictive models to identify microbiome‐based biomarkers to classify health and disease states. Finally, we address the batch effect concept and the microbiome‐specific methods for accounting for or correcting them.

Unveiling the gut microbiota and metabolite profiles in guinea pigs with form deprivation myopia through 16S rRNA gene sequencing and untargeted metabolomics

“…Microbiomics and metabolomics play pivotal roles in identifying gut microbiota and their corresponding metabolites. The former typically employs 16S rRNA gene sequencing, primarily to evaluate microbiota diversity and abundance [ 28 ]. Meanwhile, metabolomics enables the simultaneous detection of overall changes in biological system metabolites, often utilizing LC-MS as a common method for non-targeted metabolite detection [ 29 ].…”

The gut microbiomes of Channel Island foxes and island spotted skunks exhibit fine‐scale differentiation across host species and island populations

“…However, we still observed significantly lower diversity in samples sequenced on sequencing plate CIF_S08 compared to the other two plates (i.e., CIF_S09 and CIF_S10). While this batch effect did not preclude us from discovering meaningful biological insights about the microbial ecology of island foxes and island spotted skunks, it does highlight the risk of batch effects in amplicon sequencing datasets, as noted by other authors(Regueira- Iglesias et al, 2023;Wang & LêCao, 2020).…”

Are there any completely sterile organs or tissues in the human body? Is there any sacred place?

“…In most studies, the presence of microorganisms has been investigated by sequencing their 16S or their internal transcribed spacer (ITS) ribosomal DNA (rDNA) (Figure 1 ), leading to the identification of prokaryotes and fungi, respectively (Regueira‐Iglesias et al., 2023 ). The rDNA sequencing has several advantages, as it is easy and cheap to perform, and bioinformatic analysis is also well established.…”