Wang Yanling, Tangpricha Vin, Gewirtz Andrew
Center for Inflammation, Immunity, & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, Georgia.
Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.
bioRxiv. 2025 Aug 22:2025.08.22.671784. doi: 10.1101/2025.08.22.671784.
Illumina's MiSeq platform is a common approach in 16S-based microbiome analysis. Such usage is self-perpetuating in that many studies seek to employ widely used approaches to facilitate comparison of their results to existing literature. Yet, a range of factors, including cost and equipment availability can necessitate alternate approaches. For example, use of a Nano kit, lowers reagent costs by over 60% while others may only have access to entry-level sequencers such as Illumina's iSeq. The extent to which these approaches would impact results and subsequently conclusions is unknown. Attempting to address this question from the literature is complicated in that various studies not only use distinct cohorts but also differ in the reagents/methodologies to used to isolate DNA and generate sequencing libraries. Hence, we sequenced a single 16S rRNA gene amplicon library derived from 60 fecal samples, collected during a dietary supplement intervention study via MiSeq, MiseqNano, and iSeq. We evaluated platform performance by several key measurements: alpha diversity, beta diversity, taxonomic composition, and differential taxonomic abundance analysis. We found that iSeq outperformed MiSeq-Nano in alpha diversity and differential abundance detection, while MiSeq-Nano provided better taxonomic resolution than iSeq. Most importantly, all platforms showed similar core biological patterns in alpha and beta diversity and overall taxonomic composition. Thus, MiSeq, MiseqNano, and iSeq are likely to yield the same biological conclusions although specific questions and logistical consideration may favor one of these approaches.
Illumina公司的MiSeq平台是基于16S的微生物组分析中的常用方法。这种用法会自我延续,因为许多研究试图采用广泛使用的方法,以便将其结果与现有文献进行比较。然而,一系列因素,包括成本和设备可用性,可能需要采用替代方法。例如,使用Nano试剂盒可将试剂成本降低60%以上,而其他一些研究可能只能使用入门级测序仪,如Illumina公司的iSeq。这些方法对结果以及随后结论的影响程度尚不清楚。从文献中试图解决这个问题很复杂,因为各种研究不仅使用不同的队列,而且在用于分离DNA和生成测序文库的试剂/方法上也有所不同。因此,我们对一个单一的16S rRNA基因扩增子文库进行了测序,该文库来自于在一项膳食补充剂干预研究期间通过MiSeq、MiseqNano和iSeq收集的60份粪便样本。我们通过几个关键指标评估了平台性能:α多样性、β多样性、分类组成和差异分类丰度分析。我们发现,在α多样性和差异丰度检测方面,iSeq的表现优于MiSeq-Nano,而MiSeq-Nano提供了比iSeq更好的分类分辨率。最重要的是,所有平台在α和β多样性以及整体分类组成方面都显示出相似的核心生物学模式。因此,MiSeq、MiseqNano和iSeq可能会得出相同的生物学结论,尽管特定的问题和后勤考虑可能会倾向于这些方法中的某一种。