Abstract

Background

Susceptibility to Vibrio cholerae infection is affected by blood group, age, and preexisting immunity, but these factors only partially explain who becomes infected. A recent study used 16S ribosomal RNA amplicon sequencing to quantify the composition of the gut microbiome and identify predictive biomarkers of infection with limited taxonomic resolution.

Methods

To achieve increased resolution of gut microbial factors associated with V. cholerae susceptibility and identify predictors of symptomatic disease, we applied deep shotgun metagenomic sequencing to a cohort of household contacts of patients with cholera.

Results

Using machine learning, we resolved species, strains, gene families, and cellular pathways in the microbiome at the time of exposure to V. cholerae to identify markers that predict infection and symptoms. Use of metagenomic features improved the precision and accuracy of prediction relative to 16S sequencing. We also predicted disease severity, although with greater uncertainty than our infection prediction. Species within the genera Prevotella and Bifidobacterium predicted protection from infection, and genes involved in iron metabolism were also correlated with protection.

Conclusion

Our results highlight the power of metagenomics to predict disease outcomes and suggest specific species and genes for experimental testing to investigate mechanisms of microbiome-related protection from cholera.

中文翻译：

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在前瞻性队列研究中使用宏基因组学预测霍乱弧菌感染和疾病严重程度

摘要

背景

对霍乱弧菌感染的易感性受血型、年龄和预先存在的免疫力的影响，但这些因素只能部分解释谁会被感染。最近的一项研究使用 16S 核糖体 RNA 扩增子测序来量化肠道微生物组的组成，并以有限的分类学分辨率识别感染的预测性生物标志物。

方法

为了提高与霍乱弧菌易感性相关的肠道微生物因素的分辨率并确定症状性疾病的预测因子，我们将深度鸟枪法宏基因组测序应用于一组霍乱患者的家庭接触者。

结果

使用机器学习，我们在接触霍乱弧菌时解决了微生物组中的物种、菌株、基因家族和细胞通路，以确定预测感染和症状的标记。宏基因组特征的使用提高了相对于 16S 测序的预测精度和准确性。我们还预测了疾病的严重程度，尽管比我们的感染预测具有更大的不确定性。普雷沃氏菌属和双歧杆菌属内的物种预示着对感染的保护作用，参与铁代谢的基因也与保护作用相关。

结论

我们的研究结果突出了宏基因组学预测疾病结果的能力，并建议用于实验测试的特定物种和基因，以研究微生物组相关的霍乱保护机制。