Oak Ridge Institute for Science and Education, Center for Disease Control, Atlanta, GA, United States.
Animal Biosciences and Biotechnology Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, United States.
Front Cell Infect Microbiol. 2023 Feb 8;13:928353. doi: 10.3389/fcimb.2023.928353. eCollection 2023.
The gut microbiome is an integral partner in host health and plays a role in immune development, altered nutrition, and pathogen prevention. The mycobiome (fungal microbiome) is considered part of the rare biosphere but is still a critical component in health. Next generation sequencing has improved our understanding of fungi in the gut, but methodological challenges remain. Biases are introduced during DNA isolation, primer design and choice, polymerase selection, sequencing platform selection, and data analyses, as fungal reference databases are often incomplete or contain erroneous sequences.
Here, we compared the accuracy of taxonomic identifications and abundances from mycobiome analyses which vary among three commonly selected target gene regions (18S, ITS1, or ITS2) and the reference database (UNITE - ITS1, ITS2 and SILVA - 18S). We analyze multiple communities including individual fungal isolates, a mixed mock community created from five common fungal isolates found in weanling piglet feces, a purchased commercial fungal mock community, and piglet fecal samples. In addition, we calculated gene copy numbers for the 18S, ITS1, and ITS2 regions of each of the five isolates from the piglet fecal mock community to determine whether copy number affects abundance estimates. Finally, we determined the abundance of taxa from several iterations of our in-house fecal community to assess the effects of community composition on taxon abundance.
Overall, no marker-database combination consistently outperformed the others. Internal transcribed space markers were slightly superior to 18S in the identification of species in tested communities, but , a common member of piglet gut communities, was not amplified by ITS1 and ITS2 primers. Thus, ITS based abundance estimates of taxa in piglet mock communities were skewed while 18S marker profiles were more accurate. displayed the most stable copy numbers (83-85) while displayed significant variability (90-144) across gene regions.
This study underscores the importance of preliminary studies to assess primer combinations and database choice for the mycobiome sample of interest and raises questions regarding the validity of fungal abundance estimates.
肠道微生物组是宿主健康的重要伙伴,在免疫发育、营养改变和病原体预防中发挥作用。真菌组(真菌微生物组)被认为是稀有生物群的一部分,但仍然是健康的关键组成部分。下一代测序提高了我们对肠道真菌的理解,但方法学挑战仍然存在。在 DNA 分离、引物设计和选择、聚合酶选择、测序平台选择和数据分析过程中会产生偏差,因为真菌参考数据库通常不完整或包含错误的序列。
在这里,我们比较了三种常用目标基因区域(18S、ITS1 或 ITS2)和参考数据库(UNITE-ITS1、ITS2 和 SILVA-18S)中不同的真菌组分析的分类鉴定准确性和丰度。我们分析了多个群落,包括单个真菌分离株、从仔猪粪便中发现的五种常见真菌分离株组成的混合模拟群落、购买的商业真菌模拟群落和仔猪粪便样本。此外,我们计算了仔猪粪便模拟群落中五种真菌分离株的 18S、ITS1 和 ITS2 区域的基因拷贝数,以确定拷贝数是否影响丰度估计。最后,我们确定了我们内部粪便群落的几个迭代的分类丰度,以评估群落组成对分类丰度的影响。
总体而言,没有一种标记-数据库组合始终优于其他组合。在测试群落中,内转录间隔区标记在物种鉴定方面略优于 18S,但 ITS1 和 ITS2 引物不能扩增常见的仔猪肠道群落成员。因此,仔猪模拟群落中基于 ITS 的分类丰度估计存在偏差,而 18S 标记谱则更准确。在所有基因区域中, 显示出最稳定的拷贝数(83-85),而 显示出显著的变异性(90-144)。
这项研究强调了在对感兴趣的真菌组样本进行研究之前,进行初步研究以评估引物组合和数据库选择的重要性,并提出了关于真菌丰度估计有效性的问题。