• 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • 2021-03
  • br HP infection HPI and gastric mucosal


    3.3. HP infection (HPI) and gastric mucosal dysbiosis
    To investigate whether HP colonisation influences the overall struc-ture and composition of the gastric microbiota in specific microhabitats, we examined changes in the gastric microbiota in patients with histo-pathological HP+ and H. pylori negative (HP−). Approximately 70% of GC patients were diagnosed as histopathological HP+. Except for tumoral tissues, our results found a tendency towards a reduction in bacterial 3X FLAG (lower in the HP+ group; higher in the HP− group; Fig. 5a–c), while the observed species and Chao1, but not PD whole tree, were significantly higher in the normal HP− group (Fig. 5d–f) than those in both normal and peritumoral tissues. Interest-ingly, PCoA divided the gastric microbiota into different bacterial clus-ters between HP+ and HP− groups in normal and peritumoral microbiota (Fig. 5g–h), but not in tumoral microbiota (Fig. 5i). Com-bined with the higher HP colonisation found in these microhabitats, our results indicated that HPI may be one of the major determinants for the bacterial diversity of the gastric microbiota. The rarefaction curves showed that the richness of the gastric microbiota in HP− groups was significantly higher than that in HP+ groups (Fig. 5j). The
    Fig. 2. Different bacterial taxa among the three stomach microhabitats. Comparisons of the relative abundance of dominant bacterial taxa at the level of bacterial phylum (a), family (b) and genus (c). LEfSe identifies the taxa with the greatest differences in abundance among the three stomach microhabitats (d). Only the taxa meeting a significant LDA threshold value of N2 are shown (e). Nine differentially abundant bacterial species were also identified among the three microhabitats (p b .05, f; Mann-Whitney U tests). Data are presented as mean ± standard deviation. Mann-Whitney U tests were used to analyse variation among the three stomach microhabitats. §, p b .05 between normal and peritumoral tissues; +, p b .05 between peritumoral and tumoral tissues; *, p b .05 between normal and tumoral tissues.
    dominant phyla of the gastric microbiota are shown in Fig. 5k, with a higher Proteobacteria/Firmicutes ratio in HP+ groups of normal and peritumoral tissues compared to matched HP− groups. Despite these samples being histopathologically HP−, the Helicobacteraceae family could also be detected by sequencing, especially in the tumoral microbi-ota (Fig. 5l).
    To identify specific changes of the gastric microbiota that correlated with HPI in each GC microhabitat, we compared the composition of the gastric microbiota between HP+ and HP− samples using LEfSe and STAMP. Consistent with the previous diversity analyses, normal and peritumoral microbiota exhibited similar changing patterns (Figs. S9a and S10a), whereas more altered bacterial phylotypes were found in normal microbiota after HPI. However, the altered phylotypes in tu-moral microbiota were mostly non-dominant microorganisms, except Helicobacter (Fig. S11a). The community composition was further dem-onstrated by the significant differences between the HP+ and HP− groups in each stomach microhabitat using STAMP (Figs. S9b, S10b and S11b). At the species level, P. copri, B. cereus and B. uniformis were 
    enriched in the normal HP− group, while P. copri, Bacteroides plebeius, Akkermansia muciniphila, B. uniformis and B. fragilis were enriched in the peritumoral HP− group. However, only P. acnes and two non-dominant species, such as Acinetobacter schindleri and B. stercoris, were enriched in the tumoral HP− group. In addition, these oscillating genera within each tumoral microhabitat are shown in the heatmaps, with a gradual increase of Shannon in both the HP+ and HP− groups (Figs. S12a–b, S13a–b, and S14a–b). Notably, our data demonstrate that HP is negatively correlated with Shannon regardless of the stomach microhabitat, which confirms the critical roles of HP in bacterial diver-sity of the gastric microbiota (Figs. S12c, S13c and S14c). ROC analysis was performed to assess the values of gastric microbiota profiling as a diagnostic tool to discriminate between HP+ and HP−. Without HP in-cluded, other differential genera provided an area under the curve (AUC) in the ROC analysis of 0.796 in normal microbiota, 0.693 in peritumoral microbiota, and 0.700 in tumoral microbiota to distinguish HPI (Figs. S12d, S13d, S14d). Our present data suggest that HPI contrib-utes to gastric dysbiosis in stomach microhabitats.
    Fig. 3. Correlation strengths of the abundant gastric microbiota in different stomach microhabitats. Correlation network of the abundant gastric microbiota in normal microhabitat (a), peritumoral microhabitats (b) and tumoral microhabitats (c). The correlation coefficients were calculated with the Sparse Correlations for Compositional data algorithm (SparCC). Cytoscape version 3.4.0 was used for network construction. Red and green lines represent positive and negative correlations, respectively. The correlation network became simpler.