mSystemsMicrobiologyPeer-reviewed journal article
Adaptation of Enterococcus faecalis to intestinal mucus revealed by a human colonic organoid model
Sofya MikhalevaiD, Po-Long HsiaoiD, Amanzhol KurmasheviD, Caleb M. AndersoniD, Cristina Colomer‐WinteriD, Julia Alicia BoosiD, Pei Yi ChooiD, Julia L. E. WillettiD, Andreas R. HierlemanniD, Kimberly A. KlineiD, Alexandre PersatiD
Abstract
The human gastrointestinal tract hosts a diverse population of microorganisms that have a significant impact on host health. Among this population, Enterococcus faecalis (Ef) represents a common member of intestinal microbiota colonizing humans early in life, but which can also opportunistically infect its host. Despite its importance in human health, investigations of its physiological adaptation to the mucosal environment remain limited. Building on recent advances in tissue engineering, we here leverage human colonic organoids (colonoids) to investigate the Efs mechanisms of mucosal surface colonization across space and time. Using high-resolution microscopy, we visualized Ef growth within the natively formed colonic mucus layer in colonoids. Leveraging a custom perfusion chamber, we tracked Ef growth within the mucus of live colonoids over time under flow, which revealed specific colonization strategies, including biofilm-like microcolony formation. To identify Ef fitness determinants in this niche, we implemented transposon insertion sequencing (Tn-seq) in the natively formed mucus of live colonoids. This approach revealed a large fitness rearrangement compared to typical liquid culture, mainly involving metabolic activity and regulatory response during mucosal colonization, as well as factors that may contribute to colony formation at the mucosal surface. Altogether, our results show important physiological and biophysical adaptation of Ef to the mucosal surface that are not captured by in vitro conditions and that cannot be revealed in vivo at high resolution.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- approach: experimental assay
- Citations
- 3
- FWCI
- 6.16
- Field percentile
- top 4%
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