Multi-omics analysis of host-microbiome interactions in a mouse model of congenital hepatic fibrosis.

IF 4 2区 生物学 Q2 MICROBIOLOGY
Mengfan Jiao, Ye Sun, Zixing Dai, Xiaoxue Hou, Xizhi Yin, Qingling Chen, Rui Liu, Yuwen Li, Chuanlong Zhu
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引用次数: 0

Abstract

Background: Congenital hepatic fibrosis (CHF) caused by mutations in the polycystic kidney and hepatic disease 1 (PKHD1) gene is a rare genetic disorder with poorly understood pathogenesis. We hypothesized that integrating gut microbiome and metabolomic analyses could uncover distinct host-microbiome interactions in CHF mice compared to wild-type controls.

Methods: Pkhd1del3-4/del3-4 mice were generated using CRISPR/Cas9 technology. Fecal samples were collected from 11 Pkhd1del3-4/del3-4 mice and 10 littermate wild-type controls. We conducted a combined study using 16 S rDNA sequencing for microbiome analysis and untargeted metabolomics. The gut microbiome and metabolome data were integrated using Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO), which helped identify key microbial and metabolic features associated with CHF.

Results: CHF mouse model was successfully established. Our analysis revealed that the genera Mucispirillum, Eisenbergiella, and Oscillibacter were core microbiota in CHF, exhibiting significantly higher abundance in Pkhd1del3-4/del3-4 mice and strong positive correlations among them. Network analysis demonstrated robust associations between the gut microbiome and metabolome. Multi-omics dimension reduction analysis demonstrated that both the microbiome and metabolome could effectively distinguish CHF mice from controls, with area under the curve of 0.883 and 0.982, respectively. A significant positive correlation was observed between the gut microbiome and metabolome, highlighting the intricate relationship between these two components.

Conclusion: This study identifies distinct metabolic and microbiome profiles in Pkhd1del3-4/del3-4 mice. Multi-omics analysis effectively differentiates CHF mice from controls and identified potential biomarkers. These findings indicate that gut microbiota and metabolites are integral to the pathogenesis of CHF, offering novel insights into the disease mechanism.

先天性肝纤维化小鼠模型中宿主-微生物组相互作用的多组学分析。
背景:先天性肝纤维化(CHF)由多囊肾和肝脏疾病1 (PKHD1)基因突变引起,是一种罕见的遗传性疾病,发病机制尚不清楚。我们假设,与野生型对照相比,整合肠道微生物组和代谢组学分析可以揭示CHF小鼠中不同的宿主-微生物组相互作用。方法:采用CRISPR/Cas9技术制备Pkhd1del3-4/del3-4小鼠。收集了11只Pkhd1del3-4/del3-4小鼠和10只同窝野生型对照小鼠的粪便样本。我们使用16s rDNA测序进行微生物组分析和非靶向代谢组学的联合研究。肠道微生物组和代谢组数据通过使用潜在成分(DIABLO)的生物标志物发现数据集成分析进行整合,这有助于确定与CHF相关的关键微生物和代谢特征。结果:成功建立CHF小鼠模型。我们的分析显示,Mucispirillum属、Eisenbergiella属和Oscillibacter属是CHF的核心菌群,在Pkhd1del3-4/del3-4小鼠中丰度显著较高,且它们之间呈强正相关。网络分析表明,肠道微生物组和代谢组之间存在强大的关联。多组学降维分析表明,微生物组和代谢组均能有效区分CHF小鼠与对照组,曲线下面积分别为0.883和0.982。肠道微生物组和代谢组之间观察到显著的正相关,突出了这两个组成部分之间的复杂关系。结论:本研究确定了Pkhd1del3-4/del3-4小鼠不同的代谢和微生物谱。多组学分析可以有效地将CHF小鼠与对照组区分开来,并鉴定出潜在的生物标志物。这些发现表明,肠道微生物群和代谢物是CHF发病机制的组成部分,为疾病机制提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Microbiology
BMC Microbiology 生物-微生物学
CiteScore
7.20
自引率
0.00%
发文量
280
审稿时长
3 months
期刊介绍: BMC Microbiology is an open access, peer-reviewed journal that considers articles on analytical and functional studies of prokaryotic and eukaryotic microorganisms, viruses and small parasites, as well as host and therapeutic responses to them and their interaction with the environment.
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