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  • br The overall structure of the gastric microbiota is


    The overall structure of the gastric microbiota is the result of dy-namic interactions between CCK-8 members. A SparCC algorithm with FDR adjustments was employed to generate correlation-based mi-crobial interaction networks based on the relative abundance of OTUs across the three microhabitats (Fig. 3). The correlation networks formed different bacterial clusters in the three groups, with a more complex network of interactions in normal microhabitats than that in peritumoral and tumoral microhabitats, especially within or between the predominant Proteobacteria and Firmicutes phyla. The most domi-nant member, Helicobacter, was negatively correlated with Prevotella, Bacteroides, Faecalibacterium, Phascolarctobacterium and Roseburia. Those genera showed mainly positive correlations within the same bac-terial clusters. The genera of Halomonas, Shewanella, Methylobacterium and Sphingomonas demonstrated strong positive correlations in normal microbiota. However, most of these correlations were no longer signif-icant in peritumoral and tumoral microbiota, especially the interactions between Helicobacter and other genera in the two stomach microhabi-tats. One new, strong negative correlation was formed between Helicobacter and Halomonas in the peritumoral microbiota. We also ob-served that other correlations between different genera were weakened or even lost in the tumoral microbiota.
    3.2. Microhabitat-specific gastric microbiota across different GC stages and types
    To identify whether the gastric microbiota was different based on GC stages, we examined the taxonomic differences between early-stage and late-stage GC in stomach microhabitats. We enrolled 142 early-stage and 134 late-stage patients, including 112/118, 118/129, and 116/113 for normal, peritumoral, and tumoral tissues, respectively. In-terestingly, the bacterial diversity was not significantly different be-tween two stages in the same microhabitat (Fig. 4a–d). Decreased diversity in peritumoral microbiota and decreased richness in peritumoral and tumoral microhabitats were observed in both stages.
    Table 2
    Comparison of phylotype coverage and diversity estimation of the 16S rRNA gene libraries at 97% similarity.
    a The operational taxonomic units (OTUs) were defined at the 97% similarity level.
    Fig. 1. The diversity and richness of the gastric microbiota in different stomach microhabitats. The diversity indices, such as Shannon (a), Simpson (b) and Heip evenness (c), and the richness indices, such as ACE (d), observed species (e) and PD whole tree (f), were used to evaluate the overall structure of the gastric microbiota in the three stomach microhabitats. Data are presented as mean ± standard deviation. Unpaired t-tests (two-tailed) were used to analyse variation among the three stomach microhabitats. Rarefaction curves were used to estimate the richness (at a 97% level of similarity) of the gastric microbiota among the three groups (g). The vertical axis shows the number of OTUs expected after sampling the number of tags or sequences shown on the horizontal axis. Rank abundance curves of bacterial OTUs derived from the three groups, which indicated that the majority of the OTUs were present at low abundance in the gastric microbiota samples with greater sequencing depth. (h). The Venn diagram illustrates the overlap of OTUs in the gastric microbiota among the three micro-habitats (i).
    In addition, PCoA could not distinguish stage-related changes in these groups based on the unweighted UniFrac distance, weighted UniFrac distance and Bray-Curtis distance (Fig. 4e–j). Altered profiles of the gas-tric microbiota showed similar trends across different stages (Fig. S4a– c). We also found that P. acnes, S. anginosus, P. copri and Sphingomonas yabuuchiae were different among the three microhabitats in the same GC stage (Fig. 4k–n). LEfSe showed subtle clade differences among three early-stage and late-stage GC microhabitats (Figs. S5 and S6).
    Overall, 96 intestinal-type patients, 56 diffuse-type patients and 124 mixed-type patients were included. Shannon was clearly lower in the peritumoral microhabitat, and Chao 1, ACE, PD whole tree and observed species were also significantly decreased in peritumoral and tumoral microhabitats, when compared between the same GC types (Fig. S7). In stomach microhabitats, several non-dominant bacterial phylotypes were different between intestinal and diffuse GC types (Fig. S8). How-ever, there was no significant difference in the composition of the gas-tric microbiota between intestinal- and diffuse-GC types in the same stomach microhabitat. In combination with GC stages, these data sug-gested that the specific stomach microhabitats affect the diversity and composition of the gastric microbiota, regardless of GC type.