Menon Nitasha D, Poudel Saugat, Sastry Anand V, Rychel Kevin, Szubin Richard, Dillon Nicholas, Tsunemoto Hannah, Hirose Yujiro, Nair Bipin G, Kumar Geetha B, Palsson Bernhard O, Nizet Victor
School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India.
Division of Host-Microbe Systems and Therapeutics, Department of Pediatrics, University of California, San Diego, La Jolla, California, USA.
mSystems. 2024 Feb 20;9(2):e0060623. doi: 10.1128/msystems.00606-23. Epub 2024 Jan 8.
causes severe infections in humans, resists multiple antibiotics, and survives in stressful environmental conditions due to modulations of its complex transcriptional regulatory network (TRN). Unfortunately, our global understanding of the TRN in this emerging opportunistic pathogen is limited. Here, we apply independent component analysis, an unsupervised machine learning method, to a compendium of 139 RNA-seq data sets of three multidrug-resistant international clonal complex I strains (AB5075, AYE, and AB0057). This analysis allows us to define 49 independently modulated gene sets, which we call iModulons. Analysis of the identified iModulons reveals validating parallels to previously defined biological operons/regulons and provides a framework for defining unknown regulons. By utilizing the iModulons, we uncover potential mechanisms for a RpoS-independent general stress response, define global stress-virulence trade-offs, and identify conditions that may induce plasmid-borne multidrug resistance. The iModulons provide a model of the TRN that emphasizes the importance of transcriptional regulation of virulence phenotypes in . Furthermore, they suggest the possibility of future interventions to guide gene expression toward diminished pathogenic potential.IMPORTANCEThe rise in hospital outbreaks of multidrug-resistant infections underscores the urgent need for alternatives to traditional broad-spectrum antibiotic therapies. The success of as a significant nosocomial pathogen is largely attributed to its ability to resist antibiotics and survive environmental stressors. However, there is limited literature available on the global, complex regulatory circuitry that shapes these phenotypes. Computational tools that can assist in the elucidation of 's transcriptional regulatory network architecture can provide much-needed context for a comprehensive understanding of pathogenesis and virulence, as well as for the development of targeted therapies that modulate these pathways.
它会在人类中引发严重感染，对多种抗生素具有抗性，并且由于其复杂的转录调控网络（TRN）的调节作用，能在压力环境条件下存活。不幸的是，我们对这种新兴机会致病菌的TRN的整体了解有限。在此，我们将独立成分分析（一种无监督机器学习方法）应用于三种耐多药国际克隆复合体I菌株（AB5075、AYE和AB0057）的139个RNA测序数据集的汇编。该分析使我们能够定义49个独立调节的基因集，我们将其称为iModulons。对已识别的iModulons的分析揭示了与先前定义的生物学操纵子/调控子的有效相似之处，并为定义未知调控子提供了框架。通过利用iModulons，我们揭示了一种不依赖RpoS的一般应激反应的潜在机制，定义了全局应激 - 毒力权衡，并确定了可能诱导质粒介导的多药耐药性的条件。iModulons提供了一个TRN模型，强调了毒力表型转录调控在……中的重要性。此外，它们还暗示了未来进行干预以引导基因表达降低致病潜力的可能性。重要性耐多药感染在医院的爆发增加，凸显了迫切需要传统广谱抗生素治疗的替代方法。作为一种重要的医院病原体取得成功，很大程度上归因于其抵抗抗生素和在环境应激源中存活的能力。然而，关于塑造这些表型的全局、复杂调控电路的文献有限。能够协助阐明……转录调控网络结构的计算工具，可以为全面理解发病机制和毒力以及开发调节这些途径的靶向治疗提供急需的背景信息。
