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基于基因组和 STRING 数据库联合应用的海氏不动杆菌 H4 的群体感应(QS)调控靶标预测。

Quorum Sensing (QS)-regulated target predictions of Hafnia alvei H4 based on the joint application of genome and STRING database.

机构信息

School of Food Science and Technology, Dalian Polytechnic University, Dalian, China; Liaoning Key Lab for Aquatic Processing Quality and Safety, Dalian, China.

Liaoning Key Lab for Aquatic Processing Quality and Safety, Dalian, China.

出版信息

Food Res Int. 2022 Jul;157:111356. doi: 10.1016/j.foodres.2022.111356. Epub 2022 May 14.

DOI:10.1016/j.foodres.2022.111356
PMID:35761618
Abstract

In this study, we sequenced and characterized the genome of H. alvei to grasp the genetic basis of its physiological activities, including QS, metabolism, virulence and antibiotic resistance, and then mapped these functional gene clusters obtained from KEGG pathways to the STRING database to predict the QS-regulated targets in these pathways. H. alvei was found to possess 63 QS-related genes, most of which were closely related to amino acid metabolism, especially methionine pathway, but were not directly related to carbon and energy metabolism. Furthermore, the adhesion gene clusters were closely relevant to the QS gene clusters as well as to the infection gene clusters, while only one node (KdsD) was predicted between the QS gene clusters and infection gene clusters, suggesting that QS might influence the infection by regulating adhesion. QS might confer cross-resistance to microorganisms not only by regulating the formation of biofilms but also by affecting the efflux of antibiotics. In addition, the interspecies and intraspecies patterns of absence/presence for QS and its target genes were determined to shed light on the conservation of the QS regulatory mechanism among the phylogenetically related species. Taken together, the proposed methodology could expand the spectrum of possible applications of genome-based analysis to decipher the basic metabolic relationship of a microorganism, especially when studying new isolates.

摘要

在本研究中,我们对 H. alvei 的基因组进行了测序和特征分析,以了解其生理活动的遗传基础,包括 QS、代谢、毒力和抗生素耐药性,然后将这些从 KEGG 途径获得的功能基因簇映射到 STRING 数据库,以预测这些途径中 QS 调控的靶标。研究发现,H. alvei 拥有 63 个与 QS 相关的基因,其中大多数与氨基酸代谢密切相关,特别是蛋氨酸途径,但与碳和能量代谢没有直接关系。此外,黏附基因簇与 QS 基因簇以及感染基因簇密切相关,而仅预测到 QS 基因簇和感染基因簇之间存在一个节点(KdsD),表明 QS 可能通过调节黏附来影响感染。QS 不仅可以通过调节生物膜的形成来赋予微生物交叉耐药性,还可以通过影响抗生素的外排来实现。此外,还确定了 QS 及其靶基因的种间和种内缺失/存在模式,以阐明 QS 调节机制在系统发育相关物种中的保守性。综上所述,所提出的方法可以扩展基于基因组的分析在破译微生物基本代谢关系方面的应用范围,尤其是在研究新分离株时。

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