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A repository of microbial marker genes related to human health and diseases for host phenotype prediction using microbiome data

机译：与使用微生物组数据的宿主表型预测的人体健康和疾病相关的微生物标记基因的储存库

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The microbiome research is going through an evolutionary transition from focusing on the characterization of reference microbiomes associated with different environments/hosts to the translational applications, including using microbiome for disease diagnosis, improving the efficacy of cancer treatments, and prevention of diseases (e.g., using probiotics). Microbial markers have been identified from microbiome data derived from cohorts of patients with different diseases, treatment responsiveness, etc, and often predictors based on these markers were built for predicting host phenotype given a microbiome dataset (e.g., to predict if a person has type 2 diabetes given his or her microbiome data). Unfortunately, these microbial markers and predictors are often not published so are not reusable by others. In this paper, we report the curation of a repository of microbial marker genes and predictors built from these markers for microbiome-based prediction of host phenotype, and a computational pipeline called Mi2P (from Microbiome to Phenotype) for using the repository. As an initial effort, we focus on microbial marker genes related to two diseases, type 2 diabetes and liver cirrhosis, and immunotherapy efficacy for two types of cancer, non-small-cell lung cancer (NSCLC) and renal cell carcinoma (RCC). We characterized the marker genes from metagenomic data using our recently developed subtractive assembly approach. We showed that predictors built from these microbial marker genes can provide fast and reasonably accurate prediction of host phenotype given microbiome data. As understanding and making use of microbiome data (our second genome) is becoming vital as we move forward in this age of precision health and precision medicine, we believe that such a repository will be useful for enabling translational applications of microbiome data.
机译：微生物组研究正在经历一种进化转变，从重点关注与不同环境/宿主相关的参考微生物体的表征，包括使用微生物组进行疾病诊断，提高癌症治疗的疗效，以及预防疾病（例如，使用益生菌）。已经从源自不同疾病的患者群组的微生物组数据鉴定了微生物标记，并且通常基于这些标志物的常规预测因子用于预测给定微生物组数据集（例如，预测某人有2型的宿主表型（例如，预测）糖尿病鉴于他或她的微生物组数据）。不幸的是，这些微生物标记和预测因子通常不会被公布，因此不可用其他人重复使用。在本文中，我们报告了从这些标志物中构建的微生物标记基因和预测器的核酸库，用于基于微生物组的宿主表型预测，以及用于使用储存库的MI2P（从微生物组到表型）的计算管道。作为最初的努力，我们专注于与两种疾病，2型糖尿病和肝硬化相关的微生物标志物基因，以及两种类型的癌症，非小细胞肺癌（NSCLC）和肾细胞癌（RCC）的免疫治疗疗效。我们使用我们最近开发的减料装配方法表征来自偏见数据的标记基因。我们展示由这些微生物标记基因构建的预测因子可以提供给定微磁组数据的宿主表型的快速且合理地预测。由于了解和利用微生物组数据（我们的第二个Genome）正变得至关重要，因为我们在这种精确的健康和精确药物的岁月上前进，我们认为这种储存库将有助于实现微生物组数据的翻译应用。

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