Quantitative Metagenomics and the Vaginal Microbiome of Preterm Birth

项目总结/摘要 卡拉汉实验室开发了定量和计算方法，提高了精度， 标记基因和宏基因组测序方法的准确性和再现性，并实施这些 开源和积极支持的软件中的方法。卡拉汉实验室与其他 研究小组调查宿主相关微生物群落在各种健康问题中的作用， 特别关注阴道微生物组在早产中的作用。 标记基因和宏基因组测序方法已经彻底改变了人类微生物组的研究， 但是通过这些技术测量的微生物分类群的相对丰度被系统地扭曲（或 “有偏见”）从真正的相对丰度的实验和类群的具体因素，我们不明白。 在接下来的五年里，我们打算通过一个多部分的方法来解决宏基因组测序中的偏差问题。 一个程序，包括开发和验证宏基因组学中偏差的解释机制模型 实验，量化下游分析方法对宏基因组学偏差的敏感性， 不受偏见影响的新分析方法，以及开发开源软件，使研究人员能够 将有偏差的标记基因和宏基因组学测量校正到它们的真实值。 最近，标记基因和宏基因组测序方法已经揭示， 孕妇可以预测早产的风险。然而，在具体的研究之间存在分歧， 早产风险的微生物特征目前限制了这些结果的转化。我们打算开发密集的 在数百个国家中，阴道微生物群的纵向分布与亚种分类分辨率 怀孕。我们将在妊娠早期尽可能确定早产风险的精确生物标志物， 候选分类群，可以作为治疗干预的一部分，以减少早产率为目标。 我们将综合更大的证据基础上这一主题，同时控制不同的宏基因组学 不同研究中的偏差，以确定早产风险的可重复生物标志物。我们将整合 阴道微生物群的纵向分布与宿主对构建的响应的其他组学测量 阴道微生物群失调和早产之间潜在致病途径的证据。 通过开发计算和统计方法，将微生物组的测量值校正到其真实值， 值，卡拉汉实验室寻求提高精度和准确性，更广泛的研究 社区可以描述人类微生物组，从而加速我们对微生物组的理解- 相关的健康状况和微生物组疗法的发展，改善人类健康。

Project Summary/Abstract The Callahan laboratory develops quantitative and computational methods that improve the precision, accuracy and reproducibility of marker-gene and metagenomics sequencing methods, and implements those methods in open-source and actively supported software. The Callahan laboratory collaborates with other research groups to investigate the role of host-associated microbial communities in various health problems, with a particular focus on the role of the vaginal microbiome preterm birth. Marker-gene and metagenomic sequencing methods have revolutionized the study of the human microbiome, but the relative abundances of microbial taxa measured by these technologies are systematically distorted (or “biased”) from the true relative abundances by experiment- and taxa-specific factors we do not understand. Over the next five years we intend to solve the problem of bias in metagenomic sequencing via a multi-part program that includes developing and validating an explanatory mechanistic model of bias in metagenomics experiments, quantifying the sensitivity of downstream analysis methods to metagenomics bias and creating new analysis methods unaffected by bias, and developing open-source software that allows researchers to correct biased marker-gene and metagenomics measurements to their true values. Recently, marker-gene and metagenomic sequencing methods have revealed that the vaginal microbiome of pregnant women can predict risk of preterm birth. However, disagreements between studies on the specific microbial signatures of preterm risk currently limit translation of these results. We intend to develop dense longitudinal profiles with sub-species taxonomic resolution of the vaginal microbiota in hundreds of pregnancies. We will define precise biomarkers of preterm risk as early in possible in pregnancy, and identify candidate taxa that could be targeted as part of therapeutic interventions to reduce the rate of preterm birth. We will synthesize the larger evidence base on this topic while controlling for the different metagenomics biases in different studies in order to identify reproducible biomarkers of preterm birth risk. We will integrate the longitudinal profiles of the vaginal microbiota with other omics measurements of host response to build evidence for potential causative pathways between disturbances in the vaginal microbiota and preterm birth. By developing computational and statistical methods that correct measurements of the microbiome to their true values, the Callahan laboratory seeks to improve the precision and accuracy with which the wider research community can characterize the human microbiome, thereby accelerating our understanding of microbiome- related health conditions and the development of microbiome therapies that improve human health.