Fox James Douglas, Sims Austin, Ross Morgan, Bettag Jeffery, Wilder Alexandra, Natrop Dylan, Borsotti Alison, Kolli Sree, Mehta Shaurya, Verma Hema, Kurashima Kento, Manithody Chandrashekhara, Verma Arun, Jain Ajay
Department of Pediatrics, Saint Louis University, St. Louis, MO 63103, USA.
Medical College of Wisconsin-Green Bay, De Pere, WI 54115, USA.
Microbiol Res (Pavia). 2024 Dec;15(4):2554-2574. doi: 10.3390/microbiolres15040170. Epub 2024 Dec 3.
Bioinformatic methodologies play a crucial role in the assessment of gut microbiota, offering advanced tools for analyzing complex microbial communities. These methodologies involve high-throughput sequencing technologies, such as 16S rRNA gene sequencing and metagenomics, which generate vast amounts of data on microbial diversity and functional potential, as well as whole-genome sequencing, which, while being more costly, has a more expansive potential. Bioinformatics tools and algorithms process these data to identify microbial taxa and quantify and elucidate their roles within the microbiome. Advanced statistical and computational models further enable the identification of microbiota patterns associated with various diseases and health conditions. Overall, bioinformatic approaches are essential for deciphering the complexities of gut microbiota so that, in the future, we may be able to discover treatments and technologies aimed at restoring or optimizing the microbiome. The goal of this review is to describe the differences in methodology and utilization of 16S versus whole-genome sequencing to address the increased understanding of the role that the gut microbiome plays in human physiology and pathology.
生物信息学方法在肠道微生物群评估中起着至关重要的作用,为分析复杂的微生物群落提供了先进的工具。这些方法包括高通量测序技术,如16S rRNA基因测序和宏基因组学,它们能生成大量关于微生物多样性和功能潜力的数据,以及全基因组测序,全基因组测序虽成本更高,但潜力更大。生物信息学工具和算法处理这些数据,以识别微生物分类群并量化和阐明它们在微生物组中的作用。先进的统计和计算模型进一步有助于识别与各种疾病和健康状况相关的微生物群模式。总体而言,生物信息学方法对于解读肠道微生物群的复杂性至关重要,以便未来我们能够发现旨在恢复或优化微生物组的治疗方法和技术。本综述的目的是描述16S测序与全基因组测序在方法和应用上的差异,以加深对肠道微生物群在人类生理学和病理学中所起作用的理解。