Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Abstract

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome's role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

Figure 1:. Flow diagram of gut microbiome sequencing.

All steps of the microbiome sequencing (sample collection to microbiome data analysis) are displayed.

Figure 2:. 16S rRNA gene amplification and quality control analysis of V3–V4 region.

(A) Representative agarose gel electrophoresis image of the 16S amplicon (PCR1, size 550 bp) and indexed PCR (PCR2, size = 630 bp) from AE.KO mice (lanes 1–3 and 7–9) and HLA-DQ8 transgenic mice (lanes 4–6 and 10–12). (B) Representative gel image of the 16S amplicon (PCR1, size = 550 bp) and indexed PCR (PCR2, size = 630 bp) of AE.KO mice (lanes 1–3 and 8–10) and HLA-DQ8 transgenic mice (lanes 4–7 and 11–12) resolved by electrophoresis. (C) Representative electropherogram of the 16S amplicon (PCR1) showed a peak region containing fragments that were sized ~550 bp. (D) Representative electropherogram of indexed PCR (PCR2) showed a peak region comprising of fragments sized ~630 bp.

Figure 3:. Quality profile of forward reads (R1, top) for two representative samples and corresponding reverse reads (R2, bottom) for the same samples.

The analysis was performed using a DADA2 pipeline, in which the x-axis shows read length (0–300 bases) and y-axis shows quality of the reads. Green line represents the median quality score, whereas the orange line represents quartiles of the quality score distribution at each base position. Forward reads (R1) always showed better quality than reverse reads (R2).

Figure 4:. Alpha diversity measures (Shannon diversity) of AE.KO mice and HLA-DQ8 transgenic mice.

Each dot represents α-diversity (Shannon diversity) in a sample from a single mouse. Shannon diversity was overall lower for AE.KO mice compared to HLA-DQ8 transgenic mice.

Figure 5:. Ordination with partial least squares-based dimension analysis plot.

The plot shows a clear separation between AE.KO mice and HLA-DQ8 transgenic mice. Each dot represents bacterial composition within a sample, and dotted eclipses indicate 80% confidence intervals. The PLS-DA plots were generated using METAGENassist.

Figure 6:. AE.KO mice showing distinct microbial community compared to HLA-DQ8 transgenic mice, with an absence of specific bacteria in AE.KO mice.

(A) Heat map combined with agglomerative hierarchical clustering showing the relative abundance of bacteria (genus level). (B) Box plot showing a normalized relative abundance of two representative bacteria (Bilophila and Rikenella) in AE.KO and HLA-DQ8 transgenic mice. Both plots were generated using METAGENassist.