香烟烟雾导致的微生物群紊乱会加重甲型流感病毒感染的严重程度。

IF 5 2区 生物学 Q1 MICROBIOLOGY mSystems Pub Date : 2024-11-20 DOI:10.1128/msystems.00790-24
Tsering Wüthrich, Simone de Brot, Veronica Richina, Nadja Mostacci, Zora Baumann, Nathan G F Leborgne, Aurélie Godel, Marco P Alves, Mohamed Bentires-Alj, Charaf Benarafa, Markus Hilty
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引用次数: 0

摘要

香烟烟雾(CS)会促进慢性肺部疾病的发展,并与流感相关疾病风险的增加有关。在这里,我们直接探讨了CS紊乱的微生物群对甲型流感病毒(IAV)感染严重程度的影响。将无特异性和机会性病原体(SOPF)的 C57BL/6J 小鼠暴露于 CS 或室内空气(RA)中 5.5 个月。然后将每只暴露的小鼠与一组受体无菌(GF)小鼠同群饲养 1 个月,以进行微生物转移。然后用 IAV 经鼻感染定植的 GF 小鼠,并监测疾病的发展。通过 16S rRNA 基因测序和细菌培养,对供体小鼠和受体小鼠的上下气道和粪便微生物群进行了纵向调查。在口咽部,链球菌科细菌在CS和RA暴露的微生物群中差异最大。对口咽和粪便微生物群的分析表明,受体小鼠有效地转移到了嗜肛小鼠,这复制了在供体小鼠中观察到的微生物群组成差异。随后的 IAV 感染表明,与对照受体小鼠相比,CS 微生物群受体小鼠在感染后 8-10 天(dpi)的体重减轻率明显更高。此外,H1N1 感染也导致微生物群组成发生重大变化,尤其是在感染后第 4 天和第 8 天。总之,与定植有正常 SOPF 微生物群的小鼠相比,带有 CS 相关微生物群的小鼠在感染 IAV 后疾病严重程度更高。我们的数据表明,除了 CS 暴露和伴随的肺部结构损伤外,CS 暴露导致的微生物扭曲可能会影响 IAV 病程的严重程度。在本研究中,我们用长期暴露于 CS 或 RA 的 SOPF 小鼠的微生物群对无菌(GF)小鼠进行定植。这样就能将紊乱微生物群的影响与实际暴露于 CS 的免疫调节效应区分开来。我们观察到,在同群饲养后,微生物群成功转移,包括从未接触过 CS 的原 GF 小鼠因接触 CS 而诱发的特定微生物群差异。然后,我们研究了 IAV 感染对原 GF 小鼠病程和微生物群的影响。我们发现,与对照组相比,带有 CS 相关微生物群的小鼠病程更长。我们推测,CS 引起的微生物群紊乱可能确实会影响甲型流感疾病的严重程度。
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Cigarette smoke-induced disordered microbiota aggravates the severity of influenza A virus infection.

Cigarette smoke (CS) promotes the development of chronic pulmonary disease and has been associated with increased risk for influenza-related illness. Here, we directly addressed the impact of CS disordered microbiota on the severity of influenza A virus (IAV) infection. Specific and opportunistic pathogen-free (SOPF) C57BL/6J mice were exposed to CS or room air (RA) for 5.5 months. Each exposed mouse was then cohoused with a group of recipient germ-free (GF) mice for 1 month for microbial transfer. Colonized GF mice were then infected intranasally with IAV and disease development was monitored. Upper and lower airway and fecal microbiota were longitudinally investigated by 16S rRNA gene sequencing and bacterial cultures in donor and recipient mice. The bacterial family Streptococcaceae accounted for the largest difference between CS- and RA-exposed microbiota in the oropharynx. Analysis of the oropharynx and fecal microbiota indicated an efficient transfer to coprophagic recipient mice, which replicated the differences in microbiota composition observed in donor mice. Subsequent IAV infection revealed significantly higher weight loss for CS microbiota recipient mice at 8-10 days post infection (dpi) compared to control recipient mice. In addition, H1N1 infection inflicted substantial changes in the microbiota composition, especially at days 4 and 8 after infection. In conclusion, mice with a CS-associated microbiota suffer from higher disease severity upon IAV infection compared to mice colonized with a normal SOPF microbiota. Our data suggest that independently of CS exposure and concomitant structural lung damage, microbial distortion due to CS exposure may impact the severity of IAV disease course.IMPORTANCEIt has been reported that chronic exposure to CS is associated with a disordered microbiota composition. In this study, we colonized germ-free (GF) mice with the microbiota from SOPF mice which were chronically exposed to CS or RA. This allowed disentangling the effect of the disordered microbiota from the immune-modulating effects of actual CS exposure. We observed a successful transfer of the microbiotas after cohousing including specific microbiota differences induced by CS exposure in formerly GF mice, which were never exposed to CS. We then investigated the effects of IAV infection on the disease course and microbiotas of formerly GF mice. We found that mice with CS-associated microbiota reveal worse disease course compared to the control group. We hypothesize that CS-induced disordering of the microbiota may, indeed, impact the severity of influenza A disease.

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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
期刊最新文献
Association of body index with fecal microbiome in children cohorts with ethnic-geographic factor interaction: accurately using a Bayesian zero-inflated negative binomial regression model. Cigarette smoke-induced disordered microbiota aggravates the severity of influenza A virus infection. Deep learning enabled integration of tumor microenvironment microbial profiles and host gene expressions for interpretable survival subtyping in diverse types of cancers. Advancing microbiome research in Māori populations: insights from recent literature exploring the gut microbiomes of underrepresented and Indigenous peoples. Pan-genome-scale metabolic modeling of Bacillus subtilis reveals functionally distinct groups.
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