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16S rRNA 基因谱分析和基因组重建揭示了用于神经退行性疾病和作为益智药的草药的群落代谢相互作用和益生元潜力。

16S rRNA gene profiling and genome reconstruction reveal community metabolic interactions and prebiotic potential of medicinal herbs used in neurodegenerative disease and as nootropics.

机构信息

UC San Diego, School of Medicine, Center of Excellence for Research and Training in Integrative Health, Department of Family Medicine and Public Health, La Jolla, California, United States of America.

Sanford Burnham Prebys Medical Discovery Institute, Bioinformatics and Structural Biology Program, La Jolla, California, United States of America.

出版信息

PLoS One. 2019 Mar 19;14(3):e0213869. doi: 10.1371/journal.pone.0213869. eCollection 2019.


DOI:10.1371/journal.pone.0213869
PMID:30889210
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6424447/
Abstract

The prebiotic potential of nervine herbal medicines has been scarcely studied. We therefore used anaerobic human fecal cultivation to investigate whether medicinal herbs commonly used as treatment in neurological health and disease in Ayurveda and other traditional systems of medicine modulate gut microbiota. Profiling of fecal cultures supplemented with either Kapikacchu, Gotu Kola, Bacopa/Brahmi, Shankhapushpi, Boswellia/Frankincense, Jatamansi, Bhringaraj, Guduchi, Ashwagandha or Shatavari by 16S rRNA sequencing revealed profound changes in diverse taxa. Principal coordinate analysis highlights that each herb drives the formation of unique microbial communities predicted to display unique metabolic potential. The relative abundance of approximately one-third of the 243 enumerated species was altered by all herbs. Additional species were impacted in an herb-specific manner. In this study, we combine genome reconstruction of sugar utilization and short chain fatty acid (SCFA) pathways encoded in the genomes of 216 profiled taxa with monosaccharide composition analysis of each medicinal herb by quantitative mass spectrometry to enhance the interpretation of resulting microbial communities and discern potential drivers of microbiota restructuring. Collectively, our results indicate that gut microbiota engage in both protein and glycan catabolism, providing amino acid and sugar substrates that are consumed by fermentative species. We identified taxa that are efficient amino acid fermenters and those capable of both amino acid and sugar fermentation. Herb-induced microbial communities are predicted to alter the relative abundance of taxa encoding SCFA (butyrate and propionate) pathways. Co-occurrence network analyses identified a large number of taxa pairs in medicinal herb cultures. Some of these pairs displayed related culture growth relationships in replicate cultures highlighting potential functional interactions among medicinal herb-induced taxa.

摘要

神经草药的益生元潜力尚未得到充分研究。因此,我们使用厌氧人体粪便培养来研究常用于阿育吠陀和其他传统医学体系治疗神经健康和疾病的草药是否能调节肠道微生物群。通过 16S rRNA 测序对补充有卡皮卡楚、积雪草、益智、希甘达普什皮、乳香/没药、檀香、苦芝麻、诃子、冬瓜子或 Shatavari 的粪便培养物进行分析,揭示了各种分类群的深刻变化。主坐标分析突出表明,每种草药都能促进独特微生物群落的形成,这些群落预计具有独特的代谢潜力。大约三分之一的 243 种被计数的物种的相对丰度被所有草药改变。额外的物种以特定于草药的方式受到影响。在这项研究中,我们将糖利用和短链脂肪酸(SCFA)途径的基因组重建与每种草药的单糖组成分析相结合,通过定量质谱法对 216 种分析的分类群进行分析,以增强对微生物群落的解释并识别潜在的微生物群重构驱动因素。总的来说,我们的结果表明,肠道微生物群既参与蛋白质和聚糖分解代谢,又提供被发酵物种消耗的氨基酸和糖底物。我们确定了有效进行氨基酸发酵的分类群,以及既能进行氨基酸发酵又能进行糖发酵的分类群。草药诱导的微生物群被预测会改变编码 SCFA(丁酸和丙酸)途径的分类群的相对丰度。共生网络分析在草药培养物中鉴定出大量的分类群对。这些对中的一些在重复培养物中显示出相关的培养生长关系,突出了草药诱导的分类群之间潜在的功能相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/23bad237b2a8/pone.0213869.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/e2c54ebb373e/pone.0213869.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/494f396b5639/pone.0213869.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/665474ce9529/pone.0213869.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/f6fa6d440e8c/pone.0213869.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/ef745e15ba9a/pone.0213869.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/feb7cea0ea57/pone.0213869.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/e250b38c3016/pone.0213869.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/8c7667384137/pone.0213869.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/23bad237b2a8/pone.0213869.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/e2c54ebb373e/pone.0213869.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/494f396b5639/pone.0213869.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/665474ce9529/pone.0213869.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/f6fa6d440e8c/pone.0213869.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/ef745e15ba9a/pone.0213869.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/feb7cea0ea57/pone.0213869.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/e250b38c3016/pone.0213869.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/8c7667384137/pone.0213869.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e5/6424447/23bad237b2a8/pone.0213869.g009.jpg

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