Biliary microbiome profiling via 16 S rRNA amplicon sequencing in patients with cholangiocarcinoma, pancreatic carcinoma and choledocholithiasis

Abstract

Recent studies have revealed that oral, gut, and intratumoral microbial dysbiosis significantly affects tumor progression, therapy resistance, and prognosis in cholangiocarcinoma (CCA) and pancreatic ductal adenocarcinoma (PDAC) patients. However, the biliary microbiome, which directly interacts with malignant tissues, remains poorly understood. In this study, we analyzed the bile microbiota from 17 CCA, 15 PDAC, and 40 choledocholithiasis (CDL) patients using bacterial 16 S rRNA and fungal ITS sequencing. Principal coordinate analysis revealed significant differences in microbial communities between the cancer and CDL groups. The microbial community structure in each group demonstrated a specific pattern. Linear discriminant analysis revealed Streptococcus, Sphingomonas, and Bacillus enrichment in CCA patients, Neisseria, Sphingomonas, and Caulobacter in PDAC patients were more prevalent compared with CDL patients. Caulobacter was more prevalent, wheares Campylobacter was less in PDAC patients than in CCA patients. Fungal DNA was detected in ~ 50% of the samples, with CCA and PDAC patients. KEGG pathway analysis revealed altered metabolic pathways, including peptidoglycan, sphingolipid, and fatty acid metabolism and bile acid metabolism, in CCA and PDAC patients. These findings highlight the potential role of the biliary microbiome in CCA and PDAC pathogenesis, offering new insights into disease mechanisms and biomarkers.

Keywords: 16S rRNA gene amplicon sequencing; Biliary Microbiome; Cholangiocarcinoma; Choledocholithiasis; Pancreatic carcinoma.

Fig. 1

Analysis of 16 S rRNA gene amplicon sequence diversity in bile samples. The Chao1 index was used to assess the impact and diversity of bacterial flora in bile samples from the CCA, CDL, and PDAC group patients.

Fig. 2

Beta shift according to the BrayCurtis test. (a) Green dots indicate the control CDL group, and red dots indicate the CCA group. (b) Green dots indicate the CDL group, and blue dots indicate the PDAC group. Beta diversity represents the degree of difference in diversity between two samples.

Fig. 3

Bacterial classes identified in bile samples from the CDL, CCA and PDAC groups. (a) Level and order (b) level classification. Each bar indicates the percentage contribution of the class-level and order-level profiles. Gates and classes represented in different colors are indicated at the bottom of the figure.

Fig. 4

(a) LefSe comparison of bacterial classification between the CCA and CDL groups. Histograms of LDA scores for the significantly more abundant bacterial groups are shown, with the CCA group in red and the CDL in green. Each analysis was performed at the genus level, but when the genus was not determined, the next hierarchy was used. (b) Relative abundance of Streptococcus in each sample. (c) Relative abundance of Clostridiales in each sample.

Fig. 5

(a) LefSe comparison of bacterial classification between the PDAC and CDL groups. Histograms of LDA scores for the significantly more abundant bacterial groups are shown, with the PDAC group in red and the CDL in green. Each analysis was performed at the genus level, but when the genus was not determined, the next hierarchy was used. (b) Relative abundance of Alphaproteobacteria in each sample. (c) Relative abundance of Clostridium in each sample.

Fig. 6

(a) LefSe comparison of bacterial classification between the CCA and PDAC groups. Histograms of LDA scores for the significantly more abundant bacterial groups are shown, with the CCA group in red and the PDAC group in green. Each analysis was performed at the genus level, but when the genus was not determined, the next hierarchy was used. (b) Relative abundance of Caulobacterales in each sample. (c) Relative abundance of Campylobacter in each sample.

Fig. 7

Classes of fungi identified in bile samples from the CDL, CCA and PDAC groups. (a) Classification of levels. Each bar shows the percentage contribution of the gate-level and class-level profiles. The classes represented by different colors are indicated at the bottom of the figure. (b) The bacterial composition in the presence or absence of fungi in cancer cases is also shown.

Fig. 8

Schematic of the KEGG pathway, with fold change (FC) calculated for the CCA and PDAC groups, respectively, on the basis of the amount of enzyme in the CDL group. Light blue represents a slightly significant difference in the CCA group, blue represents a highly significant difference in the CCA group, and red represents a highly significant difference in the PDAC group, with larger circles indicating greater gene numbers.