Single microorganism RNA sequencing of microbiomes using smRandom-Seq.

IF 13.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Ziye Xu, Yuting Wang, Wenjie Cai, Yu Chen, Yongcheng Wang
{"title":"Single microorganism RNA sequencing of microbiomes using smRandom-Seq.","authors":"Ziye Xu, Yuting Wang, Wenjie Cai, Yu Chen, Yongcheng Wang","doi":"10.1038/s41596-025-01181-5","DOIUrl":null,"url":null,"abstract":"<p><p>Bacteria colonize nearly every part of the human body and various environments, displaying remarkable diversity. Traditional population-level transcriptomics measurements provide only average population behaviors, often overlooking the heterogeneity within bacterial communities. To address this limitation, we have developed a droplet-based, high-throughput single-microorganism RNA sequencing method (smRandom-seq) that offers highly species specific and sensitive gene detection. Here we detail procedures for microbial sample preprocessing, in situ preindexed cDNA synthesis, in situ poly(dA) tailing, droplet barcoding, ribosomal RNA depletion and library preparation. The main smRandom-seq workflow, including sample processing, in situ reactions and library construction, takes ~2 days. This method features enhanced RNA coverage, reduced doublet rates and minimized ribosomal RNA contamination, thus enabling in-depth analysis of microbial heterogeneity. smRandom-seq is compatible with microorganisms from both laboratory cultures and complex microbial community samples, making it well suited for constructing single-microorganism transcriptomic atlases of bacterial strains and diverse microbial communities. This Protocol requires experience in molecular biology and RNA sequencing techniques, and it holds promising potential for researchers investigating bacterial resistance, microbiome heterogeneity and host-microorganism interactions.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1000,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Protocols","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s41596-025-01181-5","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Bacteria colonize nearly every part of the human body and various environments, displaying remarkable diversity. Traditional population-level transcriptomics measurements provide only average population behaviors, often overlooking the heterogeneity within bacterial communities. To address this limitation, we have developed a droplet-based, high-throughput single-microorganism RNA sequencing method (smRandom-seq) that offers highly species specific and sensitive gene detection. Here we detail procedures for microbial sample preprocessing, in situ preindexed cDNA synthesis, in situ poly(dA) tailing, droplet barcoding, ribosomal RNA depletion and library preparation. The main smRandom-seq workflow, including sample processing, in situ reactions and library construction, takes ~2 days. This method features enhanced RNA coverage, reduced doublet rates and minimized ribosomal RNA contamination, thus enabling in-depth analysis of microbial heterogeneity. smRandom-seq is compatible with microorganisms from both laboratory cultures and complex microbial community samples, making it well suited for constructing single-microorganism transcriptomic atlases of bacterial strains and diverse microbial communities. This Protocol requires experience in molecular biology and RNA sequencing techniques, and it holds promising potential for researchers investigating bacterial resistance, microbiome heterogeneity and host-microorganism interactions.

使用smRandom-Seq对微生物组进行单微生物RNA测序。
细菌几乎遍布人体的每个部位和各种环境,表现出惊人的多样性。传统的群体水平转录组学测量只能提供平均群体行为,往往忽略了细菌群落内的异质性。为了解决这一限制,我们开发了一种基于液滴的高通量单微生物RNA测序方法(smRandom-seq),提供高度物种特异性和敏感的基因检测。在这里,我们详细介绍了微生物样品预处理,原位预索引cDNA合成,原位聚(dA)尾化,液滴条形码,核糖体RNA消耗和文库制备的程序。smRandom-seq的主要工作流程,包括样品处理、原位反应和文库建设,大约需要2天。该方法提高了RNA覆盖率,降低了重偶体率,最大限度地减少了核糖体RNA污染,从而能够深入分析微生物异质性。smRandom-seq与实验室培养和复杂微生物群落样本的微生物兼容,使其非常适合构建细菌菌株和不同微生物群落的单微生物转录组图谱。该议定书要求具有分子生物学和RNA测序技术方面的经验,它对研究细菌耐药性、微生物组异质性和宿主-微生物相互作用的研究人员具有很大的潜力。
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
Nature Protocols
Nature Protocols 生物-生化研究方法
CiteScore
29.10
自引率
0.70%
发文量
128
审稿时长
4 months
期刊介绍: Nature Protocols focuses on publishing protocols used to address significant biological and biomedical science research questions, including methods grounded in physics and chemistry with practical applications to biological problems. The journal caters to a primary audience of research scientists and, as such, exclusively publishes protocols with research applications. Protocols primarily aimed at influencing patient management and treatment decisions are not featured. The specific techniques covered encompass a wide range, including but not limited to: Biochemistry, Cell biology, Cell culture, Chemical modification, Computational biology, Developmental biology, Epigenomics, Genetic analysis, Genetic modification, Genomics, Imaging, Immunology, Isolation, purification, and separation, Lipidomics, Metabolomics, Microbiology, Model organisms, Nanotechnology, Neuroscience, Nucleic-acid-based molecular biology, Pharmacology, Plant biology, Protein analysis, Proteomics, Spectroscopy, Structural biology, Synthetic chemistry, Tissue culture, Toxicology, and Virology.
×
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:481959085
Book学术官方微信