Zhang Bangzhou, Penton C Ryan, Xue Chao, Wang Qiong, Zheng Tianling, Tiedje James M
Center for Microbial Ecology, Michigan State University, East Lansing, Michigan, USA State Key Lab of Marine Environmental Science and Key Lab of the MOE for Coastal and Wetland Ecosystems, School of Life Sciences, Xiamen University, Xiamen, China.
Center for Microbial Ecology, Michigan State University, East Lansing, Michigan, USA.
Appl Environ Microbiol. 2015 Jul;81(13):4536-45. doi: 10.1128/AEM.00111-15. Epub 2015 Apr 24.
The sequencing chips and kits of the Ion Torrent Personal Genome Machine (PGM), which employs semiconductor technology to measure pH changes in polymerization events, have recently been upgraded. The quality of PGM sequences has not been reassessed, and results have not been compared in the context of a gene-targeted microbial ecology study. To address this, we compared sequence profiles across available PGM chips and chemistries and with 454 pyrosequencing data by determining error types and rates and diazotrophic community structures. The PGM was then used to assess differences in nifH-harboring bacterial community structure among four corn-based cropping systems. Using our suggested filters from mock community analyses, the overall error rates were 0.62, 0.36, and 0.39% per base for chips 318 and 314 with the 400-bp kit and chip 318 with the Hi-Q chemistry, respectively. Compared with the 400-bp kit, the Hi-Q kit reduced indel rates by 28 to 59% and produced one to seven times more reads acceptable for downstream analyses. The PGM produced higher frameshift rates than pyrosequencing that were corrected by the RDP FrameBot tool. Significant differences among platforms were identified, although the diversity indices and overall site-based conclusions remained similar. For the cropping system analyses, a total of 6,182 unique NifH operational taxonomic units at 5% amino acid dissimilarity were obtained. The current crop type, as well as the crop rotation history, significantly influenced the composition of the soil diazotrophic community detected.
采用半导体技术测量聚合反应中pH变化的Ion Torrent个人基因组测序仪(PGM)的测序芯片和试剂盒最近进行了升级。PGM测序的质量尚未重新评估,且在针对基因的微生物生态学研究背景下,也未对结果进行比较。为解决这一问题,我们通过确定错误类型和发生率以及固氮群落结构,比较了不同PGM芯片和化学试剂的序列图谱,并与454焦磷酸测序数据进行了比较。然后使用PGM评估了四种玉米种植系统中携带nifH基因的细菌群落结构差异。使用我们从模拟群落分析中建议的过滤方法,对于使用400bp试剂盒的318和314芯片以及使用Hi-Q化学试剂的318芯片,总体错误率分别为每碱基0.62%、0.36%和0.39%。与400bp试剂盒相比,Hi-Q试剂盒将插入缺失率降低了28%至59%,并产生了多一至七倍可用于下游分析的读数。PGM产生的移码率高于焦磷酸测序,可通过RDP FrameBot工具进行校正。尽管多样性指数和基于位点的总体结论相似,但各平台之间仍存在显著差异。对于种植系统分析,在5%氨基酸差异水平上共获得了6182个独特的NifH操作分类单元。当前的作物类型以及作物轮作历史对检测到的土壤固氮群落组成有显著影响。