与多发性硬化症小鼠模型相关的粪便微生物组PICRUSt2分析

IF 2.5 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Sean M. Schumacher, William J. Doyle, Kristina Hill, Javier Ochoa-Repáraz
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引用次数: 0

摘要

多发性硬化症(MS)是一种中枢神经系统(CNS)的衰弱性神经炎症性疾病。全球大约有200 - 300万人被认为患有多发性硬化症,人们对多发性硬化症与肠道微生物组成之间的机制联系越来越感兴趣。实验性自身免疫性脑脊髓炎(EAE)是一种小鼠中枢神经系统炎症性脱髓鞘模型,通常用于研究MS病理与微生物组的关系。既往研究表明,EAE影响肠道微生物组,改善EAE可促进肠道微生物组稳态。微生物组稳态对宿主健康至关重要,因为它有助于免疫调节并在消化道中产生生物可利用的代谢产物。除了疾病状态外,饮食、遗传和环境等因素也会影响微生物组的稳态。我们的实验室先前证明,来自不同制造商的相同遗传系的小鼠,尽管在相似的条件下饲养,其微生物组组成也存在差异。此外,这些小鼠在EAE的进展和严重程度上表现出差异,表明微生物组的差异可能导致EAE的差异。在这里,我们使用PICRUSt2来估计EAE疾病过程中不同来源的EAE小鼠在关键时间点的微生物组功能差异。对微生物组数据的重新分析揭示了微生物组预测基因表达的明显差异,这些差异与氨基酸、碳水化合物、脂质和其他代谢物的代谢不成比例地相关。我们的研究结果支持了之前关于EAE背景下微生物组变化的观察结果,并表明评估微生物组动力学将受益于分类学评估和代谢活动,从而允许更有效和全面的研究策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

PICRUSt2 Analysis of Fecal Microbiome Associated With a Murine Model of Multiple Sclerosis

PICRUSt2 Analysis of Fecal Microbiome Associated With a Murine Model of Multiple Sclerosis

Multiple sclerosis (MS) is a debilitating neuroinflammatory disease of the central nervous system (CNS). Approximately 2–3 million people globally are believed to have MS. There is growing interest in the mechanistic link between MS and gut microbiome composition. Experimental autoimmune encephalomyelitis (EAE) is a murine model of inflammatory demyelination of the CNS commonly used to investigate the pathology of MS in relation to the microbiome. Previous research has shown that EAE affects the gut microbiome, and the improvement of EAE can promote microbiome homeostasis. Microbiome homeostasis is crucial for host health, as it contributes to immune regulation and produces bioavailable metabolic products in the digestive tract. Several factors, including diet, genetics, and environment, influence microbiome homeostasis apart from disease state. Our lab previously demonstrated that mice of the same genetic line, sourced from different manufacturers, exhibit differences in microbiome composition despite being housed under similar conditions. Furthermore, these mice showed variations in EAE progression and severity, indicating that differences in the microbiome may contribute to the discrepancies in EAE. Here, we employ PICRUSt2 to estimate functional differences in the microbiomes of EAE mice from various sources at key time points during the EAE disease course. The reanalysis of our microbiome data reveals distinct differences in predicted gene expression of microbiomes that are disproportionately related to the metabolism of amino acids, carbohydrates, lipids, and other metabolites. Our findings support previous observations regarding microbiome alterations in the context of EAE and suggest that evaluating microbiome dynamics would benefit from both taxonomic assessment and metabolic activity, allowing for more effective and comprehensive research strategies.

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来源期刊
FASEB bioAdvances
FASEB bioAdvances Multiple-
CiteScore
5.40
自引率
3.70%
发文量
56
审稿时长
10 weeks
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