Sequencing, Fast and Slow: Profiling Microbiomes in Human Samples with Nanopore Sequencing

Yunseol Park, Jeesu Lee, Hyunjin Shim
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Abstract

Rapid and accurate pathogen identification is crucial in effectively combating infectious diseases. However, the current diagnostic tools for bacterial infections predominantly rely on century-old culture-based methods. Furthermore, recent research highlights the significance of host–microbe interactions within the host microbiota in influencing the outcome of infection episodes. As our understanding of science and medicine advances, there is a pressing need for innovative diagnostic methods that can identify pathogens and also rapidly and accurately profile the microbiome landscape in human samples. In clinical settings, such diagnostic tools will become a powerful predictive instrument in directing the diagnosis and prognosis of infectious diseases by providing comprehensive insights into the patient’s microbiota. Here, we explore the potential of long-read sequencing in profiling the microbiome landscape from various human samples in terms of speed and accuracy. Using nanopore sequencers, we generate native DNA sequences from saliva and stool samples rapidly, from which each long-read is basecalled in real-time to provide downstream analyses such as taxonomic classification and antimicrobial resistance through the built-in software (<12 h). Subsequently, we utilize the nanopore sequence data for in-depth analysis of each microbial species in terms of host–microbe interaction types and deep learning-based classification of unidentified reads. We find that the nanopore sequence data encompass complex information regarding the microbiome composition of the host and its microbial communities, and also shed light on the unexplored human mobilome including bacteriophages. In this study, we use two different systems of long-read sequencing to give insights into human microbiome samples in the ‘slow’ and ‘fast’ modes, which raises additional inquiries regarding the precision of this novel technology and the feasibility of extracting native DNA sequences from other human microbiomes.
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测序,快和慢:用纳米孔测序分析人类样品中的微生物组
快速准确的病原体鉴定是有效防治传染病的关键。然而,目前细菌感染的诊断工具主要依赖于已有百年历史的基于培养的方法。此外,最近的研究强调了宿主微生物群内宿主-微生物相互作用在影响感染事件结果中的重要性。随着我们对科学和医学的理解的进步,迫切需要创新的诊断方法,既能识别病原体,又能快速准确地描绘人类样本中的微生物群景观。在临床环境中,这种诊断工具将成为一种强大的预测工具,通过提供对患者微生物群的全面了解,指导传染病的诊断和预后。在这里,我们在速度和准确性方面探索了长读测序在分析各种人类样本微生物组景观方面的潜力。利用纳米孔测序仪,我们从唾液和粪便样本中快速生成天然DNA序列,通过内置软件(<12 h)实时调用每个长读段,以提供下游分析,如分类分类和抗微生物耐药性。随后,我们利用纳米孔序列数据对每个微生物物种进行深入分析,包括宿主-微生物相互作用类型和基于深度学习的未知读段分类。我们发现纳米孔序列数据包含了宿主及其微生物群落的微生物组组成的复杂信息,并揭示了包括噬菌体在内的未开发的人类移动组。在这项研究中,我们使用了两种不同的长读测序系统,以“慢”和“快”模式深入了解人类微生物组样本,这就提出了关于这种新技术的精度和从其他人类微生物组中提取天然DNA序列的可行性的额外疑问。
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