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本文引用的文献

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Metabolic reconstruction for metagenomic data and its application to the human microbiome.宏基因组数据的代谢重建及其在人类微生物组中的应用。
PLoS Comput Biol. 2012;8(6):e1002358. doi: 10.1371/journal.pcbi.1002358. Epub 2012 Jun 13.
2
Decade-long bacterial community dynamics in cystic fibrosis airways.囊性纤维化气道中长达十年的细菌群落动态。
Proc Natl Acad Sci U S A. 2012 Apr 10;109(15):5809-14. doi: 10.1073/pnas.1120577109. Epub 2012 Mar 26.
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Untangling genomes from metagenomes: revealing an uncultured class of marine Euryarchaeota.从宏基因组中解析基因组:揭示海洋广古菌中未培养的一类。
Science. 2012 Feb 3;335(6068):587-90. doi: 10.1126/science.1212665.
4
De novo metagenomic assembly reveals abundant novel major lineage of Archaea in hypersaline microbial communities.从头宏基因组组装揭示了高盐微生物群落中丰富的古菌新主要谱系。
ISME J. 2012 Jan;6(1):81-93. doi: 10.1038/ismej.2011.78. Epub 2011 Jun 30.
5
Metatranscriptomic approach to analyze the functional human gut microbiota.采用宏转录组学方法分析功能性人肠道微生物组。
PLoS One. 2011 Mar 8;6(3):e17447. doi: 10.1371/journal.pone.0017447.
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Fast identification and removal of sequence contamination from genomic and metagenomic datasets.快速识别和去除基因组和宏基因组数据集中的序列污染。
PLoS One. 2011 Mar 9;6(3):e17288. doi: 10.1371/journal.pone.0017288.
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Quality control and preprocessing of metagenomic datasets.宏基因组数据集的质量控制和预处理。
Bioinformatics. 2011 Mar 15;27(6):863-4. doi: 10.1093/bioinformatics/btr026. Epub 2011 Jan 28.
8
Nodeomics: pathogen detection in vertebrate lymph nodes using meta-transcriptomics.节点组学:利用宏转录组学检测脊椎动物淋巴结中的病原体。
PLoS One. 2010 Oct 18;5(10):e13432. doi: 10.1371/journal.pone.0013432.
9
Effect of antibiotic treatment on bacteriophage production by a cystic fibrosis epidemic strain of Pseudomonas aeruginosa.抗生素治疗对铜绿假单胞菌囊性纤维化流行株噬菌体产生的影响。
Antimicrob Agents Chemother. 2011 Jan;55(1):426-8. doi: 10.1128/AAC.01257-10. Epub 2010 Oct 25.
10
Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions.使用串联可变 16S rRNA 基因区域比较两种下一代测序技术对高度复杂微生物群落组成的解析。
Nucleic Acids Res. 2010 Dec;38(22):e200. doi: 10.1093/nar/gkq873. Epub 2010 Sep 29.

宏基因组学和宏转录组学:囊性纤维化相关病毒和微生物群落的窗口

Metagenomics and metatranscriptomics: windows on CF-associated viral and microbial communities.

作者信息

Lim Yan Wei, Schmieder Robert, Haynes Matthew, Willner Dana, Furlan Mike, Youle Merry, Abbott Katelynn, Edwards Robert, Evangelista Jose, Conrad Douglas, Rohwer Forest

机构信息

Department of Biology, San Diego State University, San Diego, CA, 92182, USA.

Computational Science Research Center, San Diego State University, San Diego, CA, 92182, USA.

出版信息

J Cyst Fibros. 2013 Mar;12(2):154-64. doi: 10.1016/j.jcf.2012.07.009. Epub 2012 Aug 28.

DOI:10.1016/j.jcf.2012.07.009
PMID:22951208
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3534838/
Abstract

BACKGROUND

Samples collected from CF patient airways often contain large amounts of host-derived nucleic acids that interfere with recovery and purification of microbial and viral nucleic acids. This study describes metagenomic and metatranscriptomic methods that address these issues.

METHODS

Microbial and viral metagenomes, and microbial metatranscriptomes, were successfully prepared from sputum samples from five adult CF patients.

RESULTS

Contaminating host DNA was dramatically reduced in the metagenomes. Each CF patient presented a unique microbiome; in some Pseudomonas aeruginosa was replaced by other opportunistic bacteria. Even though the taxonomic composition of the microbiomes is very different, the metabolic potentials encoded by the community are very similar. The viral communities were dominated by phages that infect major CF pathogens. The metatranscriptomes reveal differential expression of encoded metabolic potential with changing health status.

CONCLUSIONS

Microbial and viral metagenomics combined with microbial transcriptomics characterize the dynamic polymicrobial communities found in CF airways, revealing both the taxa present and their current metabolic activities. These approaches can facilitate the development of individualized treatment plans and novel therapeutic approaches.

摘要

背景

从囊性纤维化(CF)患者气道采集的样本通常含有大量宿主来源的核酸,这会干扰微生物和病毒核酸的回收与纯化。本研究描述了可解决这些问题的宏基因组学和宏转录组学方法。

方法

成功从5名成年CF患者的痰液样本中制备了微生物和病毒宏基因组以及微生物宏转录组。

结果

宏基因组中污染性宿主DNA显著减少。每位CF患者都呈现出独特的微生物群;在某些患者中,铜绿假单胞菌被其他机会致病菌所取代。尽管微生物群的分类组成差异很大,但群落编码的代谢潜能非常相似。病毒群落以感染主要CF病原体的噬菌体为主。宏转录组揭示了随着健康状况变化编码代谢潜能的差异表达。

结论

微生物和病毒宏基因组学与微生物转录组学相结合,可表征CF气道中发现的动态多微生物群落,揭示存在的分类群及其当前的代谢活动。这些方法有助于制定个性化治疗方案和新型治疗方法。