Hugerth Luisa W, Wefer Hugo A, Lundin Sverker, Jakobsson Hedvig E, Lindberg Mathilda, Rodin Sandra, Engstrand Lars, Andersson Anders F
KTH Royal Institute of Technology, Science for Life Laboratory, School of Biotechnology, Division of Gene Technology, Stockholm, Sweden.
Karolinska Institutet, Department of Microbiology, Tumor and Cell Biology, Science for Life Laboratory, Stockholm, Sweden.
Appl Environ Microbiol. 2014 Aug;80(16):5116-23. doi: 10.1128/AEM.01403-14. Epub 2014 Jun 13.
The taxonomic composition of a microbial community can be deduced by analyzing its rRNA gene content by, e.g., high-throughput DNA sequencing or DNA chips. Such methods typically are based on PCR amplification of rRNA gene sequences using broad-taxonomic-range PCR primers. In these analyses, the use of optimal primers is crucial for achieving an unbiased representation of community composition. Here, we present the computer program DegePrime that, for each position of a multiple sequence alignment, finds a degenerate oligomer of as high coverage as possible and outputs its coverage among taxonomic divisions. We show that our novel heuristic, which we call weighted randomized combination, performs better than previously described algorithms for solving the maximum coverage degenerate primer design problem. We previously used DegePrime to design a broad-taxonomic-range primer pair that targets the bacterial V3-V4 region (341F-805R) (D. P. Herlemann, M. Labrenz, K. Jurgens, S. Bertilsson, J. J. Waniek, and A. F. Andersson, ISME J. 5:1571-1579, 2011, http://dx.doi.org/10.1038/ismej.2011.41), and here we use the program to significantly increase the coverage of a primer pair (515F-806R) widely used for Illumina-based surveys of bacterial and archaeal diversity. By comparison with shotgun metagenomics, we show that the primers give an accurate representation of microbial diversity in natural samples.
通过例如高通量DNA测序或DNA芯片分析微生物群落的rRNA基因含量,可以推断其分类组成。此类方法通常基于使用广泛分类范围的PCR引物对rRNA基因序列进行PCR扩增。在这些分析中,使用最佳引物对于无偏差地呈现群落组成至关重要。在此,我们展示了计算机程序DegePrime,它针对多序列比对的每个位置,找到覆盖度尽可能高的简并寡聚物,并输出其在各分类单元中的覆盖度。我们表明,我们称为加权随机组合的新型启发式算法,在解决最大覆盖度简并引物设计问题上比先前描述的算法表现更好。我们之前使用DegePrime设计了一对针对细菌V3-V4区域的广泛分类范围引物对(341F-805R)(D.P.赫勒曼、M.拉布伦茨、K.于尔根斯、S.贝蒂尔松、J.J.瓦尼克和A.F.安德森,《国际微生物生态学会杂志》5:1571-1579,2011年,http://dx.doi.org/10.1038/ismej.2011.41),在此我们使用该程序显著提高了广泛用于基于Illumina的细菌和古菌多样性调查的引物对(515F-806R)的覆盖度。通过与鸟枪法宏基因组学比较,我们表明这些引物能准确呈现自然样品中的微生物多样性。