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真菌群落:肠道真菌分析方法

Mycobiome: Approaches to analysis of intestinal fungi.

作者信息

Tang Jie, Iliev Iliyan D, Brown Jordan, Underhill David M, Funari Vincent A

机构信息

Genomics Core, Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

Department of Biomedical Sciences, Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

出版信息

J Immunol Methods. 2015 Jun;421:112-121. doi: 10.1016/j.jim.2015.04.004. Epub 2015 Apr 17.

Abstract

Massively parallel sequencing (MPSS) of bacterial 16S rDNA has been widely used to characterize the microbial makeup of the human and mouse gastrointestinal tract. However, techniques for fungal microbiota (mycobiota) profiling remain relatively under-developed. Compared to 16S profiling, the size and sequence context of the fungal Internal Transcribed Spacer 1 (ITS1), the most common target for mycobiota profiling, are highly variable. Using representative gastrointestinal tract fungi to build a known "mock" library, we examine how this sequence variability affects data quality derived from Illumina Miseq and Ion Torrent PGM sequencing pipelines. Also, while analysis of bacterial 16S profiles is facilitated by the presence of high-quality well-accepted databases of bacterial 16S sequences, such an accepted database has not yet emerged to facilitate fungal ITS sequence characterization, and we observe that redundant and inconsistent ITS1 sequence representation in publically available fungal reference databases affect quantitation and annotation of species in the gut. To address this problem, we have constructed a manually curated reference database optimized for annotation of gastrointestinal fungi. This targeted host-associated fungi (THF) database contains 1817 ITS1 sequences representing sequence diversity in genera previously identified in human and mouse gut. We observe that this database consistently outperforms three common ITS database alternatives on comprehensiveness, taxonomy assignment accuracy and computational efficiency in analyzing sequencing data from the mouse gastrointestinal tract.

摘要

细菌16S核糖体DNA的大规模平行测序(MPSS)已被广泛用于表征人类和小鼠胃肠道的微生物组成。然而,真菌微生物群(真菌群)分析技术仍相对不发达。与16S分析相比,真菌内部转录间隔区1(ITS1)作为真菌群分析最常见的靶标,其大小和序列背景具有高度变异性。我们使用代表性的胃肠道真菌构建一个已知的“模拟”文库,研究这种序列变异性如何影响来自Illumina Miseq和Ion Torrent PGM测序流程的数据质量。此外,虽然高质量且被广泛接受的细菌16S序列数据库有助于细菌16S图谱分析,但尚未出现一个被广泛接受的数据库来促进真菌ITS序列的表征,并且我们观察到公共可用真菌参考数据库中ITS1序列的冗余和不一致表示会影响肠道中物种的定量和注释。为了解决这个问题,我们构建了一个针对胃肠道真菌注释进行优化的人工编辑参考数据库。这个靶向宿主相关真菌(THF)数据库包含1817个ITS1序列,代表了先前在人类和小鼠肠道中鉴定出的属的序列多样性。我们观察到,在分析小鼠胃肠道测序数据时,该数据库在全面性、分类学分配准确性和计算效率方面始终优于三种常见的ITS数据库替代品。

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