Machine Learning and Metabolic Model Guided CRISPRi Reveals a Central Role for Phosphoglycerate Mutase in Chlamydia trachomatis Persistence.
Machine Learning and Metabolic Model Guided CRISPRi Reveals a Central Role for Phosphoglycerate Mutase in Chlamydia trachomatis Persistence.
复制标题
机器学习和代谢模型引导的 CRISPRi 揭示了磷酸甘油酸变位酶在沙眼衣原体持久性中的核心作用。
DOI：
10.1101/2023.12.18.572198
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Saha,Rajib
中科院分区：
文献类型：
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作者：
Chowdhury,NiazBahar;Pokorzynski,Nick;Rucks,ElizabethA;Ouellette,ScotP;Carabeo,ReyA;Saha,Rajib
在营养匮乏的情况下，沙眼衣原体血清型L2 （CTL）从正常生长转变为非复制形式，称为持久性。目前还不清楚，坚持到底是一种适应性反应，还是缺乏这种反应。收集了营养充足和营养匮乏CTL的转录组学数据。将机器学习方法应用于转录组学数据显示，在没有任何全局应激调节剂的情况下，应激条件下CTL的全局转录组重布线。这表明CTL的应激反应是由于缺乏适应性反应机制。为了研究这对CTL代谢的影响，我们重建了CTL （iCTL278）的基因组尺度代谢模型，并将其与收集的转录组学数据进行了背景分析。通过对iCTL278的代谢瓶颈分析，我们观察到磷酸甘油酸突变酶（pgm）调节CTL进入持久性。后来发现pgm具有最高的热力学驱动力和最低的酶促成本。此外，crispr驱动的pgm敲低和色氨酸饥饿实验揭示了该基因在诱导持久性中的重要性。因此，本工作首次引入热力学和酶成本作为工具来深入了解CTL的持久性。
Upon nutrient starvation, Chlamydia trachomatis serovar L2 (CTL) shifts from its normal growth to a non-replicating form, termed persistence. It is unclear if persistence is an adaptive response or lack of it. To understand that transcriptomics data were collected for nutrient-sufficient and nutrient-starved CTL. Applying machine learning approaches on transcriptomics data revealed a global transcriptomic rewiring of CTL under stress conditions without having any global stress regulator. This indicated that CTL’s stress response is due to lack of an adaptive response mechanism. To investigate the impact of this on CTL metabolism, we reconstructed a genome-scale metabolic model of CTL (iCTL278) and contextualized it with the collected transcriptomics data. Using the metabolic bottleneck analysis on contextualized iCTL278, we observed phosphoglycerate mutase (pgm) regulates the entry of CTL to the persistence. Later, pgm was found to have the highest thermodynamics driving force and lowest enzymatic cost. Furthermore, CRISPRi-driven knockdown of pgm and tryptophan starvation experiments revealed the importance of this gene in inducing persistence. Hence, this work, for the first time, introduced thermodynamics and enzyme-cost as tools to gain deeper understanding on CTL persistence.