Yu Meng, Jia Hongmei, Zhou Chao, Yang Yong, Zhao Yang, Yang Maohua, Zou Zhongmei
Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, PR China.
Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, PR China.
J Pharm Biomed Anal. 2017 May 10;138:231-239. doi: 10.1016/j.jpba.2017.02.008. Epub 2017 Feb 10.
As a prevalent, life-threatening and highly recurrent psychiatric illness, depression is characterized by a wide range of pathological changes; however, its etiology remains incompletely understood. Accumulating evidence supports that gut microbiota affects not only gastrointestinal physiology but also central nervous system (CNS) function and behavior through the microbiota-gut-brain axis. To assess the impact of gut microbiota on fecal metabolic phenotype in depressive conditions, an integrated approach of 16S rRNA gene sequencing combined with ultra high-performance liquid chromatography-mass spectrometry (UHPLC-MS) based metabolomics was performed in chronic variable stress (CVS)-induced depression rat model. Interestingly, depression led to significant gut microbiota changes, at the phylum and genus levels in rats treated with CVS compared to controls. The relative abundances of the bacterial genera Marvinbryantia, Corynebacterium, Psychrobacter, Christensenella, Lactobacillus, Peptostreptococcaceae incertae sedis, Anaerovorax, Clostridiales incertae sedis and Coprococcus were significantly decreased, whereas Candidatus Arthromitus and Oscillibacter were markedly increased in model rats compared with normal controls. Meanwhile, distinct changes in fecal metabolic phenotype of depressive rats were also found, including lower levels of amino acids, and fatty acids, and higher amounts of bile acids, hypoxanthine and stercobilins. Moreover, there were substantial associations of perturbed gut microbiota genera with the altered fecal metabolites, especially compounds involved in the metabolism of tryptophan and bile acids. These results showed that the gut microbiota was altered in association with fecal metabolism in depressive conditions. These findings suggest that the 16S rRNA gene sequencing and LC-MS based metabolomics approach can be further applied to assess pathogenesis of depression.
作为一种常见、危及生命且极易复发的精神疾病，抑郁症具有广泛的病理变化；然而，其病因仍未完全明确。越来越多的证据支持肠道微生物群不仅影响胃肠道生理功能，还通过微生物群-肠-脑轴影响中枢神经系统（CNS）功能和行为。为了评估肠道微生物群对抑郁状态下粪便代谢表型的影响，在慢性可变应激（CVS）诱导的抑郁症大鼠模型中，采用了16S rRNA基因测序与基于超高效液相色谱-质谱联用（UHPLC-MS）的代谢组学相结合的综合方法。有趣的是，与对照组相比，抑郁症导致CVS处理的大鼠在门和属水平上肠道微生物群发生显著变化。与正常对照组相比，模型大鼠中细菌属Marvinbryantia、棒状杆菌属、嗜冷杆菌属、克里斯滕森菌属、乳杆菌属、不确定的消化链球菌科、厌氧食菌属、不确定的梭菌目和粪球菌属的相对丰度显著降低，而暂定节旋菌属和颤杆菌属则显著增加。同时，还发现抑郁大鼠的粪便代谢表型有明显变化，包括氨基酸和脂肪酸水平较低，胆汁酸、次黄嘌呤和粪胆素含量较高。此外，肠道微生物群属的扰动与粪便代谢物的改变之间存在显著关联，尤其是参与色氨酸和胆汁酸代谢的化合物。这些结果表明，在抑郁状态下，肠道微生物群与粪便代谢相关联而发生改变。这些发现表明，基于16S rRNA基因测序和LC-MS的代谢组学方法可进一步应用于评估抑郁症的发病机制。
