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Meta-analysis Reveals Potential Influence of Oxidative Stress on the Airway Microbiomes of Cystic Fibrosis Patients

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摘要 The lethal chronic airway infection of the cystic fibrosis(CF) patients is predisposed by colonization of specific CF-philic pathogens or the CF microbiomes, but key processes and reasons of the microbiome settlement in the patients are yet to be fully understood, especially their survival and metabolic dynamics from normal to diseased status under treatment. Here, we report our meta-analysis results on CF airway microbiomes based on metabolic networks reconstructed from genome information at species level. The microbiomes of CF patients appear to engage much more redox-related activities than those of controls, and by constructing a large dataset of anti-oxidative stress(anti-OS) genes, our quantitative evaluation of the anti-OS capacity of each bacterial species in the CF microbiomes confirms strong conservation of the anti-OS responses within genera and also shows that the CF pathogens have significantly higher anti-OS capacity than commensals and other typical respiratory pathogens. In addition, the anti-OS capacity of a relevant species correlates with its relative fitness for the airways of CF patients over that for the airways of controls.Moreover, the total anti-OS capacity of the respiratory microbiome of CF patients is collectively higher than that of controls, which increases with disease progression, especially after episodes of acute exacerbation and antibiotic treatment. According to these results, we propose that the increased OS in the airways of CF patients may play an important role in reshaping airway microbiomes to a more resistant status that favors the pre-infection colonization of the CF pathogens for a higher anti-OS capacity.
出处 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2019年第6期590-602,共13页 基因组蛋白质组与生物信息学报(英文版)
基金 supported by the National Key R&D Program of China(Grant No.2016YFC0903800) the National Natural Scientific Foundation of China(Grant Nos.31470180,31471237,and 31671350) supported by the National Science Foundation/Established Program to Stimulate Competitive Research(EPSCo R)(Grant No.IIA-1355423) the State of South Dakota Research Innovation Center,the Agriculture Experiment Station of South Dakota State University,and Sanford Health–South Dakota State University Collaborative Research Seed Grant Program,United States.
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