MetaCHIP: community-level horizontal gene transfer identification through the combination of best-match and phylogenetic approaches
MetaCHIP: community-level horizontal gene transfer identification through the combination of best-match and phylogenetic approaches
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MetaCHIP：通过结合最优匹配和系统发育方法进行社区水平基因转移鉴定
DOI：
10.1186/s40168-019-0649-y
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发表时间：
2019-03-04
期刊：
影响因子：
15.5
通讯作者：
Thomas, Torsten
中科院分区：
文献类型：
--
作者：
Song, Weizhi;Wemheuer, Bernd;Thomas, Torsten
背景宏基因组数据集为在微生物群落水平上研究水平基因转移（HGT）提供了机会。然而，目前的HGT检测方法不能应用于社区级数据集或需要参考基因组。在这里，我们提出了MetaCHIP，参考独立的HGT识别在社区level.ResultsAssessment MetaCHIP的性能模拟datasets显示，它可以预测HGT与不同程度的遗传分化从宏基因组数据集。结果还表明，从宏基因组数据集检测最近的基因转移（即具有低水平遗传差异的那些）在很大程度上受到读取组装步骤的影响。MetaCHIP与之前对土壤细菌的分析的比较显示，最近HGT的预测具有高度的一致性，并揭示了大量额外的非最近基因转移，这可以提供新的生物学和生态学见解。MetaCHIP在真实的宏基因组数据集上的性能评估证实了HGT在人类肠道微生物组中与抗生素耐药性相关的基因传播中的作用。进一步的测试还表明，能源的生产和转换以及碳水化合物的运输和代谢的相关功能之间的自由生活的microorganis.ConclusionMetaCHIP提供了一个机会，研究HGT之间的微生物群落的成员，因此有几个应用领域的微生物生态学和进化。MetaCHIP是用Python实现的，可以在https://github.com/songweizhi/MetaCHIP上免费获得。
BackgroundMetagenomic datasets provide an opportunity to study horizontal gene transfer (HGT) on the level of a microbial community. However, current HGT detection methods cannot be applied to community-level datasets or require reference genomes. Here, we present MetaCHIP, a pipeline for reference-independent HGT identification at the community level.ResultsAssessment of MetaCHIP's performance on simulated datasets revealed that it can predict HGTs with various degrees of genetic divergence from metagenomic datasets. The results also indicated that the detection of very recent gene transfers (i.e. those with low levels of genetic divergence) from metagenomics datasets is largely affected by the read assembly step. Comparison of MetaCHIP with a previous analysis on soil bacteria showed a high level of consistency for the prediction of recent HGTs and revealed a large number of additional non-recent gene transfers, which can provide new biological and ecological insight. Assessment of MetaCHIP's performance on real metagenomic datasets confirmed the role of HGT in the spread of genes related to antibiotic resistance in the human gut microbiome. Further testing also showed that functions related to energy production and conversion as well as carbohydrate transport and metabolism are frequently transferred among free-living microorganisms.ConclusionMetaCHIP provides an opportunity to study HGTs among members of a microbial community and therefore has several applications in the field of microbial ecology and evolution. MetaCHIP is implemented in Python and freely available at https://github.com/songweizhi/MetaCHIP.