16S rRNA microbiota profiling in physiological normal esophagus and ESCC
We compared the 16S rRNA gene of the esophageal microbiota between patients with ESCC (T) and patients with physiological normal esophagus (PN) by NGS. After sequencing and quality filtering, more than 1171914 million clean Tags were obtained corresponding to a mean of 310 OTU and clean tags 40410 per sample. The number of clean Tags was not significantly different between PN and T groups (supplementary figure S2A). To determine the number of biologically significant OTUs, we classified the OTUs of PN and T groups according to the sequences of the Greengenes Named Isolated database. The results indicated that the frequency of bacteria OTUs was major fraction in OTU classification (supplementary figure S2C). Furthermore, Venn diagram displaying the number of common and specific OTUs identified between PN and N groups (supplementary figure S2D).
The profile of esophageal microbiota demonstrates difference in physiological normal esophagus and ESCC
We computed the alpha diversity of microbes of the T and PN using the OUTs, Shannon index, Simpson index and Good’s coverage. On average, patients with ESCC had a significantly lower number of OUTs than PN esophagus (Fig. 1A and supplementary figure S2F). However, the Shannon index and Simpson index were not significantly different between the two groups (Supplementary figure S2B and E). To estimate the bacterial diversity, we used Good’s coverage estimator to determine the proportion of total bacterial species represented in samples of each group. Statistical analysis of Good’s coverage showed that T groups had significantly different numbers of species when compared with PN groups (Fig. 1B) by measuring beta diversity using both unweighted and weighted UniFrac phylogenetic distance matrices. The microbiota composition of patients with T groups was significantly different from that of PN groups (ANOSIM R = 0.7879, P = 0.001; and ANOSIM R = 0.6346, P = 0.001, for unweighted and weighted distances, respectively; Fig. 1C and D).
Age is one of the risk factors for ESCC development. Since patients with ESCC were significantly older than patients with PN esophagus in our cohorts (supplementary table S1), we next asked whether the microbial profile was different between the two groups. Overall, age factor was not influenced the microbiota profiles of full sample set (supplementary figure S3A and B). However, compared with age-matched microbiota in patient with ESCC and PN esophagus using unweighted and weighted UniFrac distance matrices, we found that microbiota composition was significant in the two clinical settings (supplementary figure S3C and D). Furthermore, in the age-matched comparisons, the microbial alpha diversity in ESCC patients was dramatic reduced (supplementary figure S3E, p = 0.001). Intriguingly, in the cancer progress comparisons, we found that patients with ESCC had significantly decreased microbial diversity than patients with PN and PreT (pre-cancer) (supplementary figure S4C). The microbiota composition of patients with T groups was significantly different from that of PN and PreT groups (ANOSIM R = 0.53029, P = 0.001; and ANOSIM R = 0.4792, P = 0.001, for unweighted and weighted distances, respectively; supplementary figure S4F and G). The relative abundance of Fusobacterium spp. gradually increased from PN esophagus to ESCC, while the abundance of Proteobacteria was decreased (Supplementary figure S4E). However, there are no statistically significant differences in the microbiota profiles of ESCC patients with gender and tumor stage (supplementary figure S4A, B, D, H and I). Altogether, these results showed that there are significant decreased in microbial diversity and composition in ESCC.
The abundance of Fusobacterium spp.affects the microbiota composition of physiological normal esophagus and ESCC
Overall, the esophageal microbiota was dominated by seven phyla: Fusobacteria (7.43%), Actinobacteria (0.7%), Bacteroidetes (28.93%), Firmicutes (35.76%), Proteobacteria (23.21%), Spirochetes (1.57%), and Thermi (1.91%). The ESCC microbiota had an over-representation of Fusobacteria (P < 0.001), Bacteroidetes (P = 0.002) and Spirochactes (P < 0.001) and lower abundance of Proteobacteria (P = 0.006) and Thermi (P = 0.004; Fig. 2A). In addition, a significant negative correlation was observed between Fusobacteria spp. and Klebsiella. spp. (r= -0.822, P < 0.001; Fig. 2B). Accordingly, the microbiota profiles of the two groups could be discriminated by the abundance of Fusobacterium spp. (Mantel correlation, r = 0.4374, P = 0.001; Fig. 2C) and Klebsiella. spp. (Mantel correlation, r = 0.5874, P = 0.001; Fig. 2D). Altogether, these data indicated that the classification of the esophageal microbial communities differs in ESCC and PN esophagus. Also, our results verify that Fusobacteria exists in the ESCC microbiota as a high abundant.
Characterized Microbial Taxa Associated With Esophageal Carcinoma Patients
We used LEfSe analysis to identify the relevant taxa responsible for the significances between clinical diagnoses. 31 taxa, including 10 genera, which was differentially abundant between T and PN groups, was identified. Based on Genus taxa in T groups, the enrichment in Aggregatibacter, Veillonella, Parvimonas, Catonella, Streptococcus, Selenomonas, Porphyromonas, Non-Fusobacterium. Fus, Lautropia, Peptococcus, Fusobacterium.spp, Peptostreptococcus, Campylobacter, Dialister, Prevotella, Treponema, and Granulicatella were observed. In addition, Treponema amylovorum, Streptococcus infantis, Prevotella nigrescens, Porphyromonas endodontalis, Veillonella dispar, Aggregatibacter segnis, Prevotella melaninogenica, Prevotella intermedia, Prevotella tannerae, Prevotella nanceiensis and Streptococcus anginosus were also significantly more abundant in ESCC by Species taxa (Fig. 3A-C).
The age-matched comparisons of the bacteria taxa in patients with ESCC and physiological normal esophagus was performed by LEfSe analysis (Supplementary figure S3G). To determine the relationships between disease-associated taxa and the abundance of Fusobacteria, we subtracted the Fusobacteria reads and re-analyzed the library from the dataset by LEfSe analysis. In support of the above, Streptococcus, and Prevotella in ESCC were enriched (supplementary figure S5). To confirm ESCC-enriched and depleted taxa, we used 16 s rRNA-seq data from a discovery cohort of ESCC. In this dataset, we found significant decreases in the abundance of Geobacillus, Anoxybacillus, Thermus, Lactocccus, Pseudomonas, Klebsiella, Blastomonas, and Acinetobacter in ESCC compared to physiological normal esophagus (Fig. 3D). To illustrate that our results were not biased by microbiota profiling pipeline, we used a second validation cohort to confirm. In agreement with the results obtained in discovery cohort, the enrichments of Selenomonas, Peptostreptococcus, Fusobacterium spp., and Acinetobacter were confirmed in 19 genera as identified by the LEfSe analysis (Fig. 3E).
Escc Demonstrates Microbial Dysbiosis
We combined the 19 relevant taxa which characterized in patients with ESCC and PN esophagus and estimated the microbial dysbiosis index (MDI). The esophageal microbiota of patients with ESCC had a higher MDI than that patients with PN esophagus both in discovery cohort and validation cohort (Fig. 4A). Moreover, similar results were also observed in age-matched subset of discovery cohort (Supplementary figure S3F). In Fig. 4B and C, we found that MDI had a significant inverse correlation with the alpha diversity (r=-0.971, P < 0.0001) and a positive correlation with the beta diversity (r = 0.3956; P < 0.001), indicating that esophageal microbiota has a high degree of dysbiosis, consistent with reduced bacterial diversity. We further assessed if MDI could be use employed to distinguish between ESCC and physiological normal esophagus. By ROC analysis, the MDI had a good performance in identifying ESCC in discovery cohort (AUC = 95.96%, Fig. 4D) and validation cohort (AUC = 93.75%, Fig. 4E). Additionally, The MDI displayed enhanced sensitivity and specificity to monitor ESCC by using single taxa (supplementary figure S6). In validation cohorts (as shown in Fig. 3E), we confirmed the differential abundance of Fusobacterium sp., Peptostreptococcus sp., Selenomonas sp. and Acinetobacter sp. We next re-calculated the MDI with these 4 genera. The data showed that microbiota was imbalanced in the discovery cohort, validation cohort and AUCs in the ROC analysis (supplementary figure S7).
Change of nitrate/nitrite reductase functions in the microbiota of ESCC
The microbial connection in ESCC and PN esophagus could be discriminated according to their function (supplementary figure S8A). The predicted KEGG pathways significantly enriched in ESCC included aminoacyl-tRNA biosynthesis, translation proteins, ribosome biogenesis, ribosome, purine metabolism, DNA repair and recombination proteins, DNA replication proteins and Chromosome (supplementary figure S8B and supplementary table S5). Accumulating evidence demonstrated that the microbiota might produce secondary metabolites, such as reactive nitrate and nitrite, which are carcinogens associated with cancer development. We next compared ESCC and PN esophagus regarding the microbial functional signatures involved in nitrate and nitrite reductase (supplementary table S6). The results indicated that the functional composition of ESCC microbiota had decreased nitrate reductase functions and nitrite reductase functions compared to the PN esophagus (Fig. 5A and B). Collectively, these data indicated that the change of nitrate and nitrite reductase functions of ESCC microbiota is present in ESCC.