一种利用高通量测序进行人类微生物群分析的方法。

Huei-Hun Elizabeth Tseng, Meredith A J Hullar, Fei Li, Johanna W Lampe, Richard Sandstrom, Audra K Johnson, Lisa L Strate, Walter L Ruzzo, John Stamatoyannopoulos
{"title":"一种利用高通量测序进行人类微生物群分析的方法。","authors":"Huei-Hun Elizabeth Tseng,&nbsp;Meredith A J Hullar,&nbsp;Fei Li,&nbsp;Johanna W Lampe,&nbsp;Richard Sandstrom,&nbsp;Audra K Johnson,&nbsp;Lisa L Strate,&nbsp;Walter L Ruzzo,&nbsp;John Stamatoyannopoulos","doi":"10.4303/mg/235646","DOIUrl":null,"url":null,"abstract":"<p><p>Study of the human microbiota in relation to human health and disease is a rapidly expanding field. To fully understand the complex relationship between the human gut microbiota and disease risks, study designs that capture the variation within and between human subjects at the population level are required, but this has been hampered by the lack of cost-effective methods to characterize this variation. Illumina sequencing is inexpensive and produces millions of reads per run, but it is unclear whether short reads can adequately represent the microbial community of a human host. In this study, we examined the utility of a profiling method, microbial nucleotide signatures (MNS), focused on low-depth sampling of the human microbiota using Ilumina short reads. This method is intended to aid in human population-based studies where large sample sizes are required to adequately capture variation in disease or phenotype differences. We found that, by calculating the nucleotide diversities along the sequenced 16S rRNA gene region, which did not require assembly or phylogenetic identification, we were able to differentiate the gut microbial nucleotide signatures of 9 healthy individuals. When we further subsampled the reads down to 40,000 reads (51 bp long) per sample, the diversity profiles were relatively unchanged. Applying MNS to a public datasets showed that it could differentiate body site differences. The scalability of our approach offers rapid classification of study participants for studies with the sample sizes required for epidemiological studies. Using MNS to classify the microbiome associated with a disease state followed by targeted in-depth sequencing will give a comprehensive understanding of the role of the microbiome in human health.</p>","PeriodicalId":90016,"journal":{"name":"Metagenomics (Cairo, Egypt)","volume":"2 ","pages":"235646"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3764493/pdf/nihms477594.pdf","citationCount":"2","resultStr":"{\"title\":\"A microbial profiling method for the human microbiota using high-throughput sequencing.\",\"authors\":\"Huei-Hun Elizabeth Tseng,&nbsp;Meredith A J Hullar,&nbsp;Fei Li,&nbsp;Johanna W Lampe,&nbsp;Richard Sandstrom,&nbsp;Audra K Johnson,&nbsp;Lisa L Strate,&nbsp;Walter L Ruzzo,&nbsp;John Stamatoyannopoulos\",\"doi\":\"10.4303/mg/235646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Study of the human microbiota in relation to human health and disease is a rapidly expanding field. To fully understand the complex relationship between the human gut microbiota and disease risks, study designs that capture the variation within and between human subjects at the population level are required, but this has been hampered by the lack of cost-effective methods to characterize this variation. Illumina sequencing is inexpensive and produces millions of reads per run, but it is unclear whether short reads can adequately represent the microbial community of a human host. In this study, we examined the utility of a profiling method, microbial nucleotide signatures (MNS), focused on low-depth sampling of the human microbiota using Ilumina short reads. This method is intended to aid in human population-based studies where large sample sizes are required to adequately capture variation in disease or phenotype differences. We found that, by calculating the nucleotide diversities along the sequenced 16S rRNA gene region, which did not require assembly or phylogenetic identification, we were able to differentiate the gut microbial nucleotide signatures of 9 healthy individuals. When we further subsampled the reads down to 40,000 reads (51 bp long) per sample, the diversity profiles were relatively unchanged. Applying MNS to a public datasets showed that it could differentiate body site differences. The scalability of our approach offers rapid classification of study participants for studies with the sample sizes required for epidemiological studies. Using MNS to classify the microbiome associated with a disease state followed by targeted in-depth sequencing will give a comprehensive understanding of the role of the microbiome in human health.</p>\",\"PeriodicalId\":90016,\"journal\":{\"name\":\"Metagenomics (Cairo, Egypt)\",\"volume\":\"2 \",\"pages\":\"235646\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3764493/pdf/nihms477594.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metagenomics (Cairo, Egypt)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4303/mg/235646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metagenomics (Cairo, Egypt)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4303/mg/235646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

研究与人类健康和疾病有关的人类微生物群是一个迅速发展的领域。为了充分了解人类肠道微生物群与疾病风险之间的复杂关系,需要在人群水平上捕获人类受试者内部和之间的变化的研究设计,但由于缺乏具有成本效益的方法来表征这种变化,这一点受到了阻碍。Illumina测序价格低廉,每次运行可产生数百万个reads,但尚不清楚短reads是否能充分代表人类宿主的微生物群落。在这项研究中,我们研究了一种分析方法的实用性,微生物核苷酸特征(MNS),重点是使用illumina短读取器对人类微生物群进行低深度采样。该方法旨在帮助基于人群的研究,其中需要大样本量以充分捕获疾病或表型差异的变化。我们发现,通过计算沿测序的16S rRNA基因区域的核苷酸多样性,不需要组装或系统发育鉴定,我们能够区分9个健康个体的肠道微生物核苷酸特征。当我们进一步采样到每个样本的40,000个reads (51 bp长)时,多样性概况相对不变。将MNS应用于公共数据集,结果表明该方法可以区分身体部位的差异。我们方法的可扩展性为流行病学研究所需的样本量的研究提供了研究参与者的快速分类。使用MNS对与疾病状态相关的微生物组进行分类,然后进行有针对性的深度测序,将全面了解微生物组在人类健康中的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A microbial profiling method for the human microbiota using high-throughput sequencing.

Study of the human microbiota in relation to human health and disease is a rapidly expanding field. To fully understand the complex relationship between the human gut microbiota and disease risks, study designs that capture the variation within and between human subjects at the population level are required, but this has been hampered by the lack of cost-effective methods to characterize this variation. Illumina sequencing is inexpensive and produces millions of reads per run, but it is unclear whether short reads can adequately represent the microbial community of a human host. In this study, we examined the utility of a profiling method, microbial nucleotide signatures (MNS), focused on low-depth sampling of the human microbiota using Ilumina short reads. This method is intended to aid in human population-based studies where large sample sizes are required to adequately capture variation in disease or phenotype differences. We found that, by calculating the nucleotide diversities along the sequenced 16S rRNA gene region, which did not require assembly or phylogenetic identification, we were able to differentiate the gut microbial nucleotide signatures of 9 healthy individuals. When we further subsampled the reads down to 40,000 reads (51 bp long) per sample, the diversity profiles were relatively unchanged. Applying MNS to a public datasets showed that it could differentiate body site differences. The scalability of our approach offers rapid classification of study participants for studies with the sample sizes required for epidemiological studies. Using MNS to classify the microbiome associated with a disease state followed by targeted in-depth sequencing will give a comprehensive understanding of the role of the microbiome in human health.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信