Search

Background & Aims Microbiota dysbiosis and mucosa-associated bacteria are involved in colorectal cancer progression. We hypothesize that an interaction between virulent pathobionts and epithelial defense promotes tumorigenesis. Methods Chemical-induced CRC mouse model was treated with antibiotics at various phases. Colonic tissues and fecal samples were collected in a time-serial mode and analyzed by gene microarray and 16S rRNA sequencing. Intraepithelial bacteria were isolated using a gentamicin resistance assay, and challenged in epithelial cultures. Results Our study showed that antibiotic treatment at midphase but not early or late phase reduced mouse tumor burden, suggesting a time-specific host–microbe interplay. A unique antimicrobial transcriptome profile showing an inverse relationship between autophagy and oxidative stress genes was correlated with a transient surge in microbial diversity and virulence emergence in mouse stool during cancer initiation. Gavage with fimA/fimH/htrA-expressing invasive Escherichia coli isolated from colonocytes increased tumor burden in recipient mice, whereas inoculation of bacteria deleted of htrA or triple genes did not. The invasive E.coli suppressed epithelial autophagy activity through reduction of microtubule-associated protein 1 light-chain 3 transcripts and caused dual oxidase 2–dependent free radical overproduction and tumor cell hyperproliferation. A novel alternating spheroid culture model was developed for sequential bacterial challenge to address the long-term changes in host–microbe interaction for chronic tumor growth. Epithelial cells with single bacterial encounter showed a reduction in transcript levels of autophagy genes while those sequentially challenged with invasive E.coli showed heightened autophagy gene expression to eliminate intracellular microbes, implicating that bacteria-dependent cell hyperproliferation could be terminated at late phases. Finally, the presence of bacterial htrA and altered antimicrobial gene expression were observed in human colorectal cancer specimens. Conclusions Invasive pathobionts contribute to cancer initiation during a key time frame by counterbalancing autophagy and oxidative stress in the colonic epithelium. Monitoring gut microbiota and antimicrobial patterns may help identify the window of opportunity for intervention with bacterium-targeted precision medicine., Graphical abstract

The cellular specificity, potency, and modular nature of bacterial protein toxins enable their application for targeted cytosolic delivery of therapeutic cargo. Efficient endosomal escape is a critical step in the design of bacterial toxin-inspired drug delivery (BTIDD) vehicles to avoid lysosomal degradation and promote optimal cargo delivery. The cytotoxic necrotizing factor (CNF) family of modular toxins represents a useful model for investigating cargo-delivery mechanisms due to the availability of many homologs with high sequence identity, their flexibility in swapping domains, and their differential activity profiles. Previously, we found that CNFy is more sensitive to endosomal acidification inhibitors than CNF1 and CNF2. Here, we report that CNF3 is even less sensitive than CNF1/2. We identified two amino acid residues within the putative translocation domain (E374 and E412 in CNFy, Q373 and S411 in CNF3) that differentiate between these two toxins. Swapping these corresponding residues in each toxin changed the sensitivity to endosomal acidification and efficiency of cargo-delivery to be more similar to the other toxin. Results suggested that trafficking to the more acidic late endosome is required for cargo delivery by CNFy but not CNF3. This model was supported by results from toxin treatment of cells in the presence of NH4Cl, which blocks endosomal acidification, and of small-molecule inhibitors EGA, which blocks trafficking to late endosomes, and ABMA, which blocks endosomal escape and trafficking to the lysosomal degradative pathway. These findings suggest that it is possible to fine-tune endosomal escape and cytosolic cargo delivery efficiency in designing BTIDD platforms.