Resistance Gene-Directed Genome Mining of 50 Aspergillus Species
Resistance Gene-Directed Genome Mining of 50 Aspergillus Species
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DOI：
10.1128/msystems.00085-19
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发表时间：
2019-07-01
期刊：
影响因子：
6.4
通讯作者：
Andersen, Mikael R.
中科院分区：
文献类型：
--
作者：
Kjaerbolling, Inge;Vesth, Tammi;Andersen, Mikael R.
真菌次级代谢产物是有价值的天然产物的丰富来源，基因组测序揭示了基因组中预测的生物合成基因簇的增殖。然而，它目前是一个不可行的任务，以表征所有的生物合成基因簇，并确定可能的用途的化合物。因此，需要一种合理的方法来确定一个简短的名单基因簇负责生产有价值的化合物。为此，几种生物活性簇包括抗性基因，其是被化合物抑制的靶基因的一部分。这种机制可以用来识别这些集群。我们已经开发了FRIGG（真菌抗性基因导向的基因组挖掘）管道，用于基于簇基因的同源模式识别这种类型的生物合成基因簇。在这项工作中，FRIGG管道使用51个曲霉属和Penkilobacterium基因组运行，鉴定了72个推定抗性基因的独特家族。该管道还鉴定了来自fellucidae B簇的先前表征的抗性基因inpE，从而验证了该方法。我们已经成功地开发了一种方法来确定推定的有价值的生物活性簇的基础上，一个特定的阻力机制。这种方法将是非常有用的，因为越来越多的基因组数据变得可用;识别和选择正确的簇产生新的有价值的化合物的艺术只会变得更加至关重要。重要性已知属于曲霉属的物种产生大量的次级代谢产物;这些化合物中的一些被用作药物，如青霉素，环孢素和他汀类药物。通过全基因组测序，很明显次级代谢产物产生的遗传潜力比预期的要大得多。随着越来越多的物种被全基因组测序，预测了数千个次级代谢物基因，并且出现了如何从这些信息中选择性地鉴定新的生物活性化合物的问题。为了解决这个问题，我们已经创建了一个管道来预测参与生产生物活性化合物的基因的基础上耐药基因假说的方法。
Fungal secondary metabolites are a rich source of valuable natural products, and genome sequencing has revealed a proliferation of predicted biosynthetic gene clusters in the genomes. However, it is currently an unfeasible task to characterize all biosynthetic gene clusters and to identify possible uses of the compounds. Therefore, a rational approach is needed to identify a short list of gene clusters responsible for producing valuable compounds. To this end, several bioactive clusters include a resistance gene, which is a paralog of the target gene inhibited by the compound. This mechanism can be used to identify these clusters. We have developed the FRIGG (fungal resistance gene-directed genome mining) pipeline for identifying this type of biosynthetic gene cluster based on homology patterns of the cluster genes. In this work, the FRIGG pipeline was run using 51 Aspergillus and Penkillium genomes, identifying 72 unique families of putative resistance genes. The pipeline also identified the previously characterized resistance gene inpE from the fellutamide B cluster, thereby validating the approach. We have successfully developed an approach to identify putative valuable bioactive clusters based on a specific resistance mechanism. This approach will be highly useful as an everincreasing amount of genomic data becomes available; the art of identifying and selecting the right clusters producing novel valuable compounds will only become more crucial.IMPORTANCE Species belonging to the Aspergillus genus are known to produce a large number of secondary metabolites; some of these compounds are used as pharmaceuticals, such as penicillin, cyclosporine, and statin. With whole-genome sequencing, it became apparent that the genetic potential for secondary metabolite production is much larger than expected. As an increasing number of species are whole-genome sequenced, thousands of secondary metabolite genes are predicted, and the question of how to selectively identify novel bioactive compounds from this information arises. To address this question, we have created a pipeline to predict genes involved in the production of bioactive compounds based on a resistance gene hypothesis approach.