Bioinformatic Methodologies in Assessing Gut Microbiota.

IF 2.2 Q3 MICROBIOLOGY
Microbiology Research Pub Date : 2024-12-01 Epub Date: 2024-12-03 DOI:10.3390/microbiolres15040170
James Douglas Fox, Austin Sims, Morgan Ross, Jeffery Bettag, Alexandra Wilder, Dylan Natrop, Alison Borsotti, Sree Kolli, Shaurya Mehta, Hema Verma, Kento Kurashima, Chandrashekhara Manithody, Arun Verma, Ajay Jain
{"title":"Bioinformatic Methodologies in Assessing Gut Microbiota.","authors":"James Douglas Fox, Austin Sims, Morgan Ross, Jeffery Bettag, Alexandra Wilder, Dylan Natrop, Alison Borsotti, Sree Kolli, Shaurya Mehta, Hema Verma, Kento Kurashima, Chandrashekhara Manithody, Arun Verma, Ajay Jain","doi":"10.3390/microbiolres15040170","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":43788,"journal":{"name":"Microbiology Research","volume":"15 4","pages":"2554-2574"},"PeriodicalIF":2.2000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12381627/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbiology Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/microbiolres15040170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/3 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

Abstract Image

Abstract Image

Abstract Image

评估肠道微生物群的生物信息学方法。
生物信息学方法在评估肠道微生物群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,它们产生了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,后者虽然成本更高,但具有更广阔的潜力。生物信息学工具和算法处理这些数据,以确定微生物分类群,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能够确定与各种疾病和健康状况相关的微生物群模式。总的来说,生物信息学方法对于破译肠道微生物群的复杂性至关重要,因此,在未来,我们可能能够发现旨在恢复或优化微生物群的治疗和技术。本综述的目的是描述16S与全基因组测序在方法和应用上的差异,以解决对肠道微生物组在人体生理和病理中的作用的进一步了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Microbiology Research
Microbiology Research MICROBIOLOGY-
CiteScore
1.90
自引率
6.70%
发文量
62
审稿时长
10 weeks
期刊介绍: Microbiology Research is an international, online-only, open access peer-reviewed journal which publishes original research, review articles, editorials, perspectives, case reports and brief reports to benefit researchers, microbiologists, physicians, veterinarians. Microbiology Research publishes ‘Clinic’ and ‘Research’ papers divided into two different skill and proficiency levels: ‘Junior’ and ‘Professional’. The aim of this four quadrant grid is to encourage younger researchers, physicians and veterinarians to submit their results even if their studies encompass just a limited set of observations or rely on basic statistical approach, yet upholding the customary sound approach of every scientific article.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信