BackgroundInflammatory bowel disease (IBD) patients experience recurrent episodes of intestinal inflammation and often follow an unpredictable disease course. Mucosal colonization with adherent-invasiveEscherichia coli(AIEC) are believed to perpetuate intestinal inflammation. However, it remains unclear if the 24-year-old AIECin-vitrodefinition fully predicts mucosal colonizationin-vivo. To fill this gap, we have developed a novel molecular barcoding approach to distinguish strain variants in the gut and have integrated this approach to explore mucosal colonization of distinct patient-derivedE. coliisolates in gnotobiotic mouse models of colitis.ResultsGerm-free inflammation-susceptible interleukin-10-deficient (Il10−/−) and inflammation-resistant WT mice were colonized with a consortia of AIEC and non-AIEC strains, then given a murine fecal transplant to provide niche competition.E. colistrains isolated from human intestinal tissue were each marked with a unique molecular barcode that permits identification and quantification by barcode-targeted sequencing. 16S rRNA sequencing was used to evaluate the microbiome response toE. colicolonization. Our data reveal that specific AIEC and non-AIEC strains reproducibly colonize the intestinal mucosa of WT andIl10−/−mice. TheseE. coliexpand inIl10−/−mice during inflammation and induce compositional dysbiosis to the microbiome in an inflammation-dependent manner. In turn, specific microbes co-evolve in inflamed mice, potentially diversifyingE. colicolonization patterns. We observed no selectivity inE. colicolonization patterns in the fecal contents, indicating minimal selective pressure in this niche from host-microbe and interbacterial interactions. Because select AIEC and non-AIEC strains colonize the mucosa, this suggests thein vitroAIEC definition may not fully predictin vivocolonization potential. Further comparison of sevenE. coligenomes pinpointed unique genomic features contained only in highly colonizing strains (two AIEC and two non-AIEC). Those colonization-associated features may convey metabolic advantages (e.g., iron acquisition and carbohydrate consumption) to promote efficient mucosal colonization.ConclusionsOur findings establish thein-vivomucosal colonizer, not necessarily AIEC, as a principal dysbiosis driver through crosstalk with host and associated microbes. Furthermore, we highlight the utility of high-throughput screens to decode thein-vivocolonization dynamics of patient-derived bacteria in murine models.