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PMID: 41718551 已发表 · ppublish 英语

Extracellular vesicles and their RNA cargo facilitate bidirectional cross-kingdom communication between human and bacterial cells.

Gut microbes ·第 18 卷 ·第 1 期 ·2026-12-31

Gröger L, Rishik S, Ludwig N, Beganovic A, Koch M, Rheinheimer S, Hart M, König P, Trampert T, Paul P, Boese A, Lehr CM, Becker SL, Fuhrmann G, Keller A, Meese E

摘要

While extracellular vesicles (EVs) are established mediators of intra-species signaling, their contribution to cross-kingdom communication remains incompletely understood. Here, we investigate the EV-mediated interactions between human colon epithelial cells and both Gram-positive and Gram-negative gut bacteria. We show that bacterial EVs (BEVs) derived from Lacticaseibacillus casei, Enterococcus faecalis, and Proteus mirabilis induce distinct transcriptomic changes in Caco-2 cells depending on the bacterial species, with up to ~6,000 differentially expressed genes, including CCL20, CXCL8, or CXCL10. Transfection of BEV-derived RNA independently induces a subset of similar effects, indicating that the EV-mediated communication is partially driven by the RNA cargo. Conversely, we demonstrate that bacteria interact with Caco-2-derived EVs and miR-192-5p, which is highly abundant (~36.4-fold higher) in EVs isolated from conditioned medium compared with EVs from unconditioned medium, with modest effects on bacterial growth. Furthermore, we show that lipid-based packaging of miR-192-5p modulates its association with the bacteria. Our findings support a conceptual model in which EVs and their RNA cargo contribute to species-dependent host-microbe interactions. This study introduces a framework for understanding EVs as cross-kingdom regulators and underscores the importance of tailored, context-specific analyses for understanding the scope of EV-mediated interactions in microbiome-host homeostasis and disease.

关键词
EV Extracellular vesicles bacteria communication cross-kingdom miRNA
文献信息
期刊
Gut microbes
期刊简称
Gut Microbes
ISSN
1949-0984
发表日期
2026-12-31
语言
英语
国家/地区
United States
NLM ID
101495343
分析服务
分析服务

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