A High-Throughput Method for Identifying Novel Genes That Influence Metabolic Pathways Reveals New Iron and Heme Regulation in Pseudomonas aeruginosa.
A High-Throughput Method for Identifying Novel Genes That Influence Metabolic Pathways Reveals New Iron and Heme Regulation in Pseudomonas aeruginosa.
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一种用于鉴定影响代谢途径的新基因的高通量方法揭示了铜绿假单胞菌中的新铁和血红素调节。
DOI：
10.1128/msystems.00933-20
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发表时间：
2021-02-02
期刊：
影响因子：
6.4
通讯作者：
Ulijasz AT
中科院分区：
文献类型：
--
作者：
Glanville DG;Mullineaux-Sanders C;Corcoran CJ;Burger BT;Imam S;Donohue TJ;Ulijasz AT
在全球范围内将基因与代谢物水平同时和更直接地联系起来的能力将为许多生物平台提供新的信息，但到目前为止一直是具有挑战性的。在这里，我们描述了一种方法来帮助解决这个问题，我们称之为“Met-Seq”(代谢物偶联TN测序)。血红素是地球上大多数生命必不可少的代谢物。细菌病原体几乎普遍需要铁来感染宿主，通常以血红素的形式获得这种营养。革兰氏阴性病原菌铜绿假单胞菌也不例外，众所周知，血红素的获取和代谢对慢性和急性感染都是至关重要的。为了揭示在这种病原体中可能与血红素代谢通量起作用的未知基因和途径，我们设计了一种基于基因组的方法，我们称之为“Met-Seq”，用于代谢物耦合的转座子测序。MET-Seq将生物传感器与荧光激活细胞分类(FACS)和大规模并行测序相结合，允许直接识别与代谢变化相关的基因。在这项工作中，我们首先构建并验证了一个用于铜绿假单胞菌的血红素生物传感器，并利用Met-Seq来识别188个可能影响细胞内血红素水平的基因。已鉴定的基因主要由以前与血红素无关的代谢途径组成，包括许多分泌的毒力效应因子，以及11个预测的小RNA(SRNAs)和核糖开关，其功能目前尚不清楚。我们验证了五个Met-Seq点击影响细胞内血红素水平；一个预测的胞浆外功能(ECF)因子，一个磷脂获取系统，血红素生物合成调节因子DNR，以及两个预测的功能未知的抗生素单加氧酶(ABM)结构域(PA0709和PA3390)。最后，我们证明了PA0709和PA3390是新的血红素结合蛋白。我们的数据表明，Met-Seq可以外推到其他具有生物传感器的生物系统和代谢物中，并为进一步探索铜绿假单胞菌和其他病原体中铁/血红素的调节和代谢提供了新的模板。重要性能够在全球范围内将基因与代谢物水平同时和更直接地联系起来，将为许多生物平台提供新的信息，但到目前为止，这一能力一直具有挑战性。在这里，我们描述了一种方法来帮助解决这个问题，我们称之为“Met-Seq”(代谢物偶联TN测序)。MET-Seq使用荧光生物传感器、荧光激活细胞分类(FACS)和下一代测序(NGS)的强大组合来快速识别影响特定细胞内代谢物水平的基因。为了验证概念，我们创建并测试了一个血红素生物传感器，然后利用Met-Seq来识别参与调节铜绿假单胞菌中的血红素的新基因。Met-Seq产生的数据主要由以前没有报道过的影响这种病原体中血红素水平的基因组成，其中两个我们验证为新的血红素结合蛋白。由于血红素是铜绿假单胞菌和大多数其他病原体感染宿主所必需的代谢物，我们的研究为潜在的抗菌治疗提供了一个新的靶点，并进一步阐明了感染、血红素摄取和血红素生物合成之间的平衡。
The ability to simultaneously and more directly correlate genes with metabolite levels on a global level would provide novel information for many biological platforms yet has thus far been challenging. Here, we describe a method to help address this problem, which we dub “Met-Seq” (metabolite-coupled Tn sequencing). Heme is an essential metabolite for most life on earth. Bacterial pathogens almost universally require iron to infect a host, often acquiring this nutrient in the form of heme. The Gram-negative pathogen Pseudomonas aeruginosa is no exception, where heme acquisition and metabolism are known to be crucial for both chronic and acute infections. To unveil unknown genes and pathways that could play a role with heme metabolic flux in this pathogen, we devised an omic-based approach we dubbed “Met-Seq,” for metabolite-coupled transposon sequencing. Met-Seq couples a biosensor with fluorescence-activated cell sorting (FACS) and massively parallel sequencing, allowing for direct identification of genes associated with metabolic changes. In this work, we first construct and validate a heme biosensor for use with P. aeruginosa and exploit Met-Seq to identify 188 genes that potentially influence intracellular heme levels. Identified genes largely consisted of metabolic pathways not previously associated with heme, including many secreted virulence effectors, as well as 11 predicted small RNAs (sRNAs) and riboswitches whose functions are not currently understood. We verify that five Met-Seq hits affect intracellular heme levels; a predicted extracytoplasmic function (ECF) factor, a phospholipid acquisition system, heme biosynthesis regulator Dnr, and two predicted antibiotic monooxygenase (ABM) domains of unknown function (PA0709 and PA3390). Finally, we demonstrate that PA0709 and PA3390 are novel heme-binding proteins. Our data suggest that Met-Seq could be extrapolated to other biological systems and metabolites for which there is an available biosensor, and provides a new template for further exploration of iron/heme regulation and metabolism in P. aeruginosa and other pathogens. IMPORTANCE The ability to simultaneously and more directly correlate genes with metabolite levels on a global level would provide novel information for many biological platforms yet has thus far been challenging. Here, we describe a method to help address this problem, which we dub “Met-Seq” (metabolite-coupled Tn sequencing). Met-Seq uses the powerful combination of fluorescent biosensors, fluorescence-activated cell sorting (FACS), and next-generation sequencing (NGS) to rapidly identify genes that influence the levels of specific intracellular metabolites. For proof of concept, we create and test a heme biosensor and then exploit Met-Seq to identify novel genes involved in the regulation of heme in the pathogen Pseudomonas aeruginosa. Met-Seq-generated data were largely comprised of genes which have not previously been reported to influence heme levels in this pathogen, two of which we verify as novel heme-binding proteins. As heme is a required metabolite for host infection in P. aeruginosa and most other pathogens, our studies provide a new list of targets for potential antimicrobial therapies and shed additional light on the balance between infection, heme uptake, and heme biosynthesis.
Shigella flexneri gluq-rs基因的表达与DKSA相关，并由转录终结子控制。
影响因子：
4.2
作者：
Caballero VC;Toledo VP;Maturana C;Fisher CR;Payne SM;Salazar JC
通讯作者：
Salazar JC