• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于OTU和ASV方法的污水处理厂系统微生物组分析——生态数据的比较解读

Microbiome Analysis via OTU and ASV-Based Pipelines-A Comparative Interpretation of Ecological Data in WWTP Systems.

作者信息

Jeske Jan Torsten, Gallert Claudia

机构信息

Faculty of Technology, Microbiology-Biotechnology, University of Applied Science Emden/Leer, 26723 Emden, Germany.

出版信息

Bioengineering (Basel). 2022 Mar 29;9(4):146. doi: 10.3390/bioengineering9040146.

DOI:10.3390/bioengineering9040146
PMID:35447706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9029325/
Abstract

Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.

摘要

通过对标记基因(如16S rRNA基因)进行非培养分析来关联群落组成与生态系统功能,是微生物生态学及其相关学科的一项主要工作。对于该领域取得的任何进展而言,结果的确定性(独立于生物信息处理)至关重要。在这项工作中,利用两条在处理技术、测序和PCR偏差时应用不同原理的流程,对嗜热厌氧共消化实验数据以及原初和废弃活性污泥原核生物群落数据进行了分析。一条流程(VSEARCH)采用聚类方法,生成单个操作分类单元(OTU),而另一条流程(DADA2)基于测序错误校正算法,生成精确的扩增子序列变体(ASV)。在生态驱动的数据分析框架内,对两条流程的结果进行了比较。两条流程都提供了具有可比性的结果,通常能得出相同的解释。然而,两种方法得出的群落组成在流程之间也存在6.75%至10.81%的差异。还观察到与样本中生物驱动的变异性相关的不一致性,这对两条流程的影响有所不同。分类归属中这些依赖流程的差异可能导致不同的结论,并干扰针对此类错误识别或未识别物种进行的任何下游分析,例如网络分析或对其各自生态系统服务的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1a9/9029325/3821d0f9be9a/bioengineering-09-00146-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1a9/9029325/f2fd6b22aab4/bioengineering-09-00146-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1a9/9029325/3821d0f9be9a/bioengineering-09-00146-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1a9/9029325/f2fd6b22aab4/bioengineering-09-00146-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1a9/9029325/3821d0f9be9a/bioengineering-09-00146-g002.jpg

相似文献

1
Microbiome Analysis via OTU and ASV-Based Pipelines-A Comparative Interpretation of Ecological Data in WWTP Systems.基于OTU和ASV方法的污水处理厂系统微生物组分析——生态数据的比较解读
Bioengineering (Basel). 2022 Mar 29;9(4):146. doi: 10.3390/bioengineering9040146.
2
Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches.对去噪器进行去噪:微生物组序列错误校正方法的独立评估。
PeerJ. 2018 Aug 8;6:e5364. doi: 10.7717/peerj.5364. eCollection 2018.
3
Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold.对偏倚进行排名:在 16S rRNA 扩增子数据分析中,OTUs 与 ASVs 的选择对多样性测量的影响大于稀疏和 OTU 同一性阈值。
PLoS One. 2022 Feb 24;17(2):e0264443. doi: 10.1371/journal.pone.0264443. eCollection 2022.
4
An independent evaluation in a CRC patient cohort of microbiome 16S rRNA sequence analysis methods: OTU clustering, DADA2, and Deblur.在结直肠癌患者队列中对微生物组16S rRNA序列分析方法进行的独立评估:OTU聚类、DADA2和Deblur。
Front Microbiol. 2023 Jul 25;14:1178744. doi: 10.3389/fmicb.2023.1178744. eCollection 2023.
5
Ecological Observations Based on Functional Gene Sequencing Are Sensitive to the Amplicon Processing Method.基于功能基因测序的生态观测对扩增子处理方法敏感。
mSphere. 2022 Aug 31;7(4):e0032422. doi: 10.1128/msphere.00324-22. Epub 2022 Aug 8.
6
Piphillin predicts metagenomic composition and dynamics from DADA2-corrected 16S rDNA sequences.Piphillin 可根据 DADA2 校正的 16S rDNA 序列预测宏基因组组成和动态。
BMC Genomics. 2020 Jan 17;21(1):56. doi: 10.1186/s12864-019-6427-1.
7
Impact of DNA Sequencing and Analysis Methods on 16S rRNA Gene Bacterial Community Analysis of Dairy Products.DNA 测序和分析方法对乳制品 16S rRNA 基因细菌群落分析的影响。
mSphere. 2018 Oct 17;3(5):e00410-18. doi: 10.1128/mSphere.00410-18.
8
Taxonomic annotation of 16S rRNA sequences of pig intestinal samples using MG-RAST and QIIME2 generated different microbiota compositions.使用 MG-RAST 和 QIIME2 对猪肠道样本的 16S rRNA 序列进行分类注释产生了不同的微生物群落组成。
J Microbiol Methods. 2021 Jul;186:106235. doi: 10.1016/j.mimet.2021.106235. Epub 2021 May 8.
9
Amplicon Sequence Variants Artificially Split Bacterial Genomes into Separate Clusters.扩增子序列变异将细菌基因组人为地分成单独的聚类。
mSphere. 2021 Aug 25;6(4):e0019121. doi: 10.1128/mSphere.00191-21. Epub 2021 Jul 21.
10
From reads to operational taxonomic units: an ensemble processing pipeline for MiSeq amplicon sequencing data.从读取到可操作分类单元:用于MiSeq扩增子测序数据的集成处理流程
Gigascience. 2017 Feb 1;6(2):1-10. doi: 10.1093/gigascience/giw017.

引用本文的文献

1
Lactulose selectively stimulates members of the gut microbiota, as determined by multi-modal activity-based sorting.通过基于多模式活性的分选确定,乳果糖可选择性刺激肠道微生物群的成员。
Gut Microbes. 2025 Dec;17(1):2525482. doi: 10.1080/19490976.2025.2525482. Epub 2025 Jun 27.
2
Distinguishing critical microbial community shifts from normal temporal variability in human and environmental ecosystems.区分人类和环境生态系统中关键微生物群落变化与正常时间变异性。
Sci Rep. 2025 May 15;15(1):16934. doi: 10.1038/s41598-025-01781-x.
3
The unresolved struggle of 16S rRNA amplicon sequencing: a benchmarking analysis of clustering and denoising methods.

本文引用的文献

1
Handling of spurious sequences affects the outcome of high-throughput 16S rRNA gene amplicon profiling.假序列的处理会影响高通量16S rRNA基因扩增子分析的结果。
ISME Commun. 2021 Jun 29;1(1):31. doi: 10.1038/s43705-021-00033-z.
2
Integrated treatment of food waste with wastewater and sewage sludge: Energy and carbon footprint analysis with economic implications.食物垃圾与废水和污水污泥的综合处理:能源与碳足迹分析及其经济影响
Sci Total Environ. 2022 Jun 15;825:154052. doi: 10.1016/j.scitotenv.2022.154052. Epub 2022 Feb 24.
3
A positive correlation between GC content and growth temperature in prokaryotes.
16S rRNA扩增子测序的未解决难题:聚类和去噪方法的基准分析
Environ Microbiome. 2025 May 13;20(1):51. doi: 10.1186/s40793-025-00705-6.
4
Prenatal PFAS exposure and outcomes related to maternal gut microbiome composition in later pregnancy.产前全氟烷基和多氟烷基物质(PFAS)暴露与妊娠后期母体肠道微生物群组成相关的结局
Environ Res. 2025 Aug 15;279(Pt 1):121709. doi: 10.1016/j.envres.2025.121709. Epub 2025 Apr 29.
5
A retrospective study on blood microbiota as a marker for cognitive decline: implications for detecting Alzheimer's disease and amnestic mild cognitive impairment in Republic of Korea.一项关于血液微生物群作为认知衰退标志物的回顾性研究:对韩国阿尔茨海默病和遗忘型轻度认知障碍检测的启示
Osong Public Health Res Perspect. 2025 Apr;16(2):141-151. doi: 10.24171/j.phrp.2024.0329. Epub 2025 Mar 24.
6
Alterations in Gut Microbiota Composition Are Associated with Changes in Emotional Distress in Children with Obstructive Sleep Apnea.肠道微生物群组成的改变与阻塞性睡眠呼吸暂停儿童情绪困扰的变化有关。
Microorganisms. 2024 Dec 18;12(12):2626. doi: 10.3390/microorganisms12122626.
7
Methodological approaches in 16S sequencing of female reproductive tract in fertility patients: a review.生育力患者女性生殖道16S测序的方法学探讨:综述
J Assist Reprod Genet. 2025 Jan;42(1):15-37. doi: 10.1007/s10815-024-03292-6. Epub 2024 Oct 21.
8
The choice of 16S rRNA gene sequence analysis impacted characterization of highly variable surface microbiota in dairy processing environments.16S rRNA 基因序列分析的选择影响了乳品加工环境中高度可变表面微生物群落的特征分析。
mSystems. 2024 Nov 19;9(11):e0062024. doi: 10.1128/msystems.00620-24. Epub 2024 Oct 21.
9
RiboSnake - a user-friendly, robust, reproducible, multipurpose and documentation-extensive pipeline for 16S rRNA gene microbiome analysis.RiboSnake——一个用于16S rRNA基因微生物组分析的用户友好、强大、可重复、多用途且文档丰富的流程。
GigaByte. 2024 Aug 31;2024:gigabyte132. doi: 10.46471/gigabyte.132. eCollection 2024.
10
ASV vs OTUs clustering: Effects on alpha, beta, and gamma diversities in microbiome metabarcoding studies.ASV 与 OTUs 聚类:对宏基因组 metabarcoding 研究中 alpha、beta 和 gamma 多样性的影响。
PLoS One. 2024 Oct 3;19(10):e0309065. doi: 10.1371/journal.pone.0309065. eCollection 2024.
原核生物中 GC 含量与生长温度呈正相关。
BMC Genomics. 2022 Feb 9;23(1):110. doi: 10.1186/s12864-022-08353-7.
4
Mechanisms Driving Microbial Community Composition in Anaerobic Co-Digestion of Waste-Activated Sewage Sludge.驱动废弃活性污泥厌氧共消化中微生物群落组成的机制
Bioengineering (Basel). 2021 Nov 30;8(12):197. doi: 10.3390/bioengineering8120197.
5
Enhancing diversity analysis by repeatedly rarefying next generation sequencing data describing microbial communities.通过重复稀疏化描述微生物群落的下一代测序数据来增强多样性分析。
Sci Rep. 2021 Nov 16;11(1):22302. doi: 10.1038/s41598-021-01636-1.
6
MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data.MicFunPred:一种从16S rRNA基因序列数据预测功能谱的保守方法。
Genomics. 2021 Nov;113(6):3635-3643. doi: 10.1016/j.ygeno.2021.08.016. Epub 2021 Aug 24.
7
Release LTP_12_2020, featuring a new ARB alignment and improved 16S rRNA tree for prokaryotic type strains.发布 LTP_12_2020,其中包括新的 ARB 比对和改进的原核模式菌株 16S rRNA 树。
Syst Appl Microbiol. 2021 Jul;44(4):126218. doi: 10.1016/j.syapm.2021.126218. Epub 2021 May 24.
8
Urban wastewater bacterial communities assemble into seasonal steady states.城市污水中的细菌群落会形成季节性稳定状态。
Microbiome. 2021 May 20;9(1):116. doi: 10.1186/s40168-021-01038-5.
9
Sequencing error profiles of Illumina sequencing instruments.Illumina测序仪的测序错误图谱。
NAR Genom Bioinform. 2021 Mar 27;3(1):lqab019. doi: 10.1093/nargab/lqab019. eCollection 2021 Mar.
10
Comparison of Two 16S rRNA Primers (V3-V4 and V4-V5) for Studies of Arctic Microbial Communities.用于北极微生物群落研究的两种16S rRNA引物(V3-V4和V4-V5)的比较
Front Microbiol. 2021 Feb 16;12:637526. doi: 10.3389/fmicb.2021.637526. eCollection 2021.