Mucosal Microbiome in Patients with Early Bowel Polyps: Inferences from Short-Read and Long-Read 16S rRNA Sequencing

Abstract

Numerous studies have correlated dysbiosis in stool microbiota with colorectal cancer (CRC); however, fewer studies have investigated the mucosal microbiome in pre-cancerous bowel polyps. The short-read sequencing of variable regions in the 16S rRNA gene has commonly been used to infer bacterial taxonomy, and this has led, in part, to inconsistent findings between studies. Here, we examined mucosal microbiota from patients who presented with one or more polyps, compared to patients with no polyps, at the time of colonoscopy. We evaluated the results obtained using both short-read and PacBio long-read 16S rRNA sequencing. Neither sequencing technology identified significant differences in microbial diversity measures between patients with or without bowel polyps. Differential abundance measures showed that amplicon sequence variants (ASVs) associated with Ruminococcus gnavus and Escherichia coli were elevated in mucosa from polyp patients, while ASVs associated with Parabacteroides merdae, Veillonella nakazawae, and Sutterella wadsworthensis were relatively decreased. Only R. gnavus was consistently identified using both sequencing technologies as being altered between patients with polyps compared to patients without polyps, suggesting differences in technologies and bioinformatics processing impact study findings. Several of the differentially abundant bacteria identified using either sequencing technology are associated with inflammatory bowel diseases despite these patients being excluded from the current study, which suggests that early bowel neoplasia may be associated with a local inflammatory niche.

Keywords: 16S rRNA sequencing; PacBio long-read sequencing; bowel polyps; gut microbiome.

Figure 1

Composition plots aggregated to the phylum level for (A) SR and (B) PB-LR data. (C) Gel electrophoresis of DNA from mucosa samples amplified with bacterial 16S-ITS-23S or 16S V1–V9 primers. Lane 1: DNA ladder. Lanes 2–4 (yellow underline) represent PCR products from stool amplified with 16S V1–V9 primers. Lanes 5–10 (blue underline) represent the PCR products from a selection of mucosal biopsy study samples amplified with 16S V1–V9 primers. Lanes 11–16 (red underline) represent PCR products from a selection of mucosal biopsy study samples amplified with 16S-ITS-23S primers. The 16S rRNA gene amplicon of interest is shown with the blue box.

Figure 2

(A) Bar chart depicting the percentage of ASVs assigned to genus and species-level taxonomy for short-read (SR), SR silva database only, and PacBio (PB) long-read (LR) platforms. Histograms for (B) SR and (C) PB-LR library sizes for 27 polyp-associated and 27 polyp-free samples.

Figure 3

Top 15 ASVs for (A) SR abundance, (B) SR prevalence, (C) PB-LR abundance, (D) PB-LR prevalence. Top 15 species for (E) SR abundance, (F) SR prevalence, (G) PB-LR abundance, and (H) PB-LR prevalence.

Figure 4

Short-read data: (A) Alpha diversity: Box plots of the Shannon diversity index, Chao1 richness estimator, and Pielou evenness index (B) Beta diversity: PCoA of the Bray–Curtis distance measure. PacBio long-read data: (C) Alpha diversity: Box plots of the Shannon diversity index, Chao1 richness estimator, and Pielou evenness index. (D) Beta diversity: PCoA of the Bray–Curtis distance measure. All data colored by polyp status.

Figure 5

Composition plots with ASVs aggregated at the phylum level for (A) SR and (B) PB-LR, set at the family level for (C) SR and (D) PB-LR data, and set at the genus level for (E) SR and (F) LR data, comparing polyp-associated and polyp-free cases.

Figure 6

Phylogenetic trees of the order Eubacteriales for (A) SR and (B) PB-LR data.

Figure 7

LEfSe differential abundance plot for (A) SR and (B) PB data sets, and ANCOMBC2 analyses for (C) SR and (D) PB-LR data, showing bacteria differentially abundant (p < 0.05) between polyp-associated and polyp-free samples. LEfSe bar plots for Ruminococcus gnavus are displayed for (E) SR and (F) PB-LR data. Each red bar indicates the relative abundance for a participant specimen. The black vertical bar separates the polyp specimens from polyp-free specimens. The black solid and dashed horizontal bars indicate the mean and median relative abundance for the two patient groups, respectively.

Figure 8

Principal Components Analysis for (A) short-read and (D) PacBio long-read data. Sparse Partial Least Squares Discriminant Analysis for (B) short-read and (E) PacBio long-read data. Each plot is colored by polyp status. Bar plots for (C) short-read and (F) PacBio long-read data: ASVs are ranked according to how influential they are in contributing to the variability in component 1 with the most important on the bottom. The color of each bar corresponds to which group (polyp or polyp-free) has the higher median for the ASV.