毒力
微生物学
生物
拉伤
艰难梭菌
毒素
病毒学
艰难梭菌毒素A
质粒
艰难梭菌毒素B
基因
遗传学
解剖
抗生素
作者
Qiwen Dong,S.R. Harper,Ethan D. McSpadden,Seong‐Ho Son,Marie-Maude Allen,Huaiying Lin,Rita Smith,Carolyn Metcalfe,Victoria Burgo,Che Woodson,Anitha Sundararajan,Amber Rose,Mary McMillin,David Morán,Jessica Little,Michael W. Mullowney,Ashley M. Sidebottom,Aimee Shen,Louis‐Charles Fortier,Eric G. Pamer
标识
DOI:10.1101/2024.05.06.592814
摘要
Clostridioides difficile (C. difficile) strains belonging to the epidemic BI/NAP1/027 (RT027) group have been associated with increased transmissibility and disease severity. In addition to the major toxin A and toxin B virulence factors, RT027 strains also encode the CDT binary toxin. Our lab previously identified a toxigenic RT027 isolate, ST1-75, that is avirulent in mice despite densely colonizing the colon. Here, we show that co-infecting mice with the avirulent ST1-75 and virulent R20291 strains protects mice from colitis due to rapid clearance of the virulent strain and persistence of the avirulent strain. Although avirulence of ST1-75 is due to a mutation in the cdtR gene, which encodes a response regulator that modulates the production of all three C. difficile toxins, the ability of ST1-75 to protect against acute colitis is not directly attributable to the cdtR mutation. Metabolomic analyses indicate that the ST1-75 strain depletes amino acids more rapidly than the R20291 strain and supplementation with amino acids ablates ST1-75 s competitive advantage, suggesting that the ST1-75 strain limits the growth of virulent R20291 bacteria by amino acid depletion. Since the germination kinetics and sensitivity to the co-germinant glycine are similar for the ST1-75 and R20291 strains, our results identify the rapidity of in vivo nutrient depletion as a mechanism providing strain-specific, virulence-independent competitive advantages to different BI/NAP1/027 strains. They also suggest that the ST1-75 strain may, as a biotherapeutic agent, enhance resistance to CDI in high-risk patients.
科研通智能强力驱动
Strongly Powered by AbleSci AI