PRJNA431248
16s rRNA sequencing of cervical cancer biopsies
The goal of this study was to explore the potential contribution of intra-tumor microbiota in the development of cervical cancer. First, we investigated the cervical microbiome via analysis of 16S rRNA. Using qPCR, we detected bacterial DNA in 121 out of 123 samples of cervical carcinoma but were only able to sequence 58 samples with higher amounts of bacterial DNA. To explore host-microbe interactions, we focused on the most abundant (>0.5%) 38 unique bacterial taxa. Next, we reconstructed a transkingdom network by integrating our group previously discovered cervical cancer gene expression network with a novel bacterial network consisting of 37 bacteria with 54 edges that were connected via 19 edges to human genes (p < 0.001 and FDR < 0.1). To pinpoint which bacteria are involved in tumor gene regulation, we have identified bacterial nodes with high bipartite betweenness centrality (biBC) between microbial and host compartments of the network. The top bottleneck microbes were represented by the families Bacillaceae, Halobacteriaceae, and Prevotellaceae. While we could not define the first two families to the species level, Prevotellaceae was assigned to Prevotella bivia. We additionally used biBC to predict host genes critical for the carcinogenetic host-microbiota interaction and found LAMP3 gene driver amongst the top 1%. Subsequent experiments validated our prediction by demonstrating increased expression of LAMP3 and TAP1 as well as STAT1, the downstream gene of LAMP3, after co-culture with Prevotella bivia. Thus, transkingdom network analysis established candidate bacteria contributing to cervical carcinogenesis through the induction of LAMP3, a central driver of the interferon-related pathway.