首页> 美国卫生研究院文献>Proceedings of the National Academy of Sciences of the United States of America >PNAS PlusFrom the Cover: Identifying personal microbiomes using metagenomic codes
【2h】

PNAS PlusFrom the Cover: Identifying personal microbiomes using metagenomic codes

机译:从封面开始:使用宏基因组代码识别个人微生物群

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。
获取外文期刊封面目录资料

摘要

Community composition within the human microbiome varies across individuals, but it remains unknown if this variation is sufficient to uniquely identify individuals within large populations or stable enough to identify them over time. We investigated this by developing a hitting set-based coding algorithm and applying it to the Human Microbiome Project population. Our approach defined body site-specific metagenomic codes: sets of microbial taxa or genes prioritized to uniquely and stably identify individuals. Codes capturing strain variation in clade-specific marker genes were able to distinguish among 100s of individuals at an initial sampling time point. In comparisons with follow-up samples collected 30–300 d later, ∼30% of individuals could still be uniquely pinpointed using metagenomic codes from a typical body site; coincidental (false positive) matches were rare. Codes based on the gut microbiome were exceptionally stable and pinpointed >80% of individuals. The failure of a code to match its owner at a later time point was largely explained by the loss of specific microbial strains (at current limits of detection) and was only weakly associated with the length of the sampling interval. In addition to highlighting patterns of temporal variation in the ecology of the human microbiome, this work demonstrates the feasibility of microbiome-based identifiability—a result with important ethical implications for microbiome study design. The datasets and code used in this work are available for download from .
机译:人类微生物组中的群落组成因个体而异,但是这种变化是否足以唯一地识别大型人群中的个体,或者是否足够稳定以随时间推移识别它们,仍然未知。我们通过开发基于匹配集的编码算法并将其应用于“人类微生物组计划”人群进行了调查。我们的方法定义了特定于身体部位的宏基因组编码:一组微生物分类群或优先考虑独特且稳定地识别个体的基因。捕获进化枝特异性标记基因中的菌株变异的代码能够在初始采样时间点区分100多个个体。与30-300 d后收集的随访样本进行比较,仍然可以使用典型身体部位的宏基因组编码来精确定位约30%的个体;巧合(假阳性)匹配很少见。基于肠道微生物组的密码非常稳定,可精确定位> 80%的个体。代码在以后的某个时间点与所有者不匹配的失败,很大程度上是由于特定微生物菌株的损失(在当前的检测极限下)而造成的,并且仅与采样间隔的长度相关。除了突出人类微生物组生态学中的时间变化模式之外,这项工作还证明了基于微生物组的可识别性的可行性-这一结果对微生物组研究设计具有重要的伦理意义。这项工作中使用的数据集和代码可从下载。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号