RNA Regulators: Formidable Modulators of Yersinia Virulence

Nuss, Aaron M.; Heroven, Ann Kathrin; Dersch, Petra

doi:10.1016/j.tim.2016.08.006

Cited by 12 publications

(9 citation statements)

References 72 publications

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“…Modeling RNA structure accurately, however, is a difficult task, both experimentally and computationally 2 . Of particular interest and challenge are regulatory systems that involve multiple functional and biologically important structures, such as natural and engineered riboswitches, riboSNitches, ribozymes, thermosensors, viral elements, protein-bound RNA, and folding pathways 3 – 10 . Often, these alternative structures are jointly present at different abundances, to confer these systems their flexibility and sensitivity in responding to diverse cellular signals.…”

Section: Introductionmentioning

confidence: 99%

Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes

Aviran

2018

Nat Commun

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RNA plays key regulatory roles in diverse cellular processes, where its functionality often derives from folding into and converting between structures. Many RNAs further rely on co-existence of alternative structures, which govern their response to cellular signals. However, characterizing heterogeneous landscapes is difficult, both experimentally and computationally. Recently, structure profiling experiments have emerged as powerful and affordable structure characterization methods, which improve computational structure prediction. To date, efforts have centered on predicting one optimal structure, with much less progress made on multiple-structure prediction. Here, we report a probabilistic modeling approach that predicts a parsimonious set of co-existing structures and estimates their abundances from structure profiling data. We demonstrate robust landscape reconstruction and quantitative insights into structural dynamics by analyzing numerous data sets. This work establishes a framework for data-directed characterization of structure landscapes to aid experimentalists in performing structure-function studies.

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Section: Introductionmentioning

confidence: 99%

Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes

Aviran

2018

Nat Commun

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“…In some of these cases, selective depletion of host transcripts was utilized. While the majority of this work has focused on in vitro infection of cells, in the past few years, analysis has expanded to include in vivo infections in the case of certain pathogens (for example, Toxoplasma gondii [ 64 ], Yersinia pseudotuberculosis [ 65 ] and Pseudomonas aeruginosa [ 66 ]). In the case of Brucella infection, Rossetti et al characterized changes in bacterial and pathogen transcriptomes, but this was performed over the course of a 4 h time period subsequent to introduction of 3 × 10 9 CFU of bacteria [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Coincidence cloning recovery of Brucella melitensis RNA from goat tissues: advancing the in vivo analysis of pathogen gene expression in brucellosis

et al. 2018

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BackgroundBrucella melitensis bacteria cause persistent, intracellular infections in small ruminants as well as in humans, leading to significant morbidity and economic loss worldwide. The majority of experiments on the transcriptional responses of Brucella to conditions inside the host have been performed following invasion of cultured mammalian cells, and do not address gene expression patterns during long-term infection.ResultsHere, we examine the application of the previously developed coincidence cloning methodology to recover and characterize B. melitensis RNA from the supramammary lymph node of experimentally-infected goats. Using coincidence cloning, we successfully recovered Brucella RNA from supramammary lymph nodes of B. melitensis-infected goats at both short-term (4 weeks) and long-term (38 weeks) infection time points. Amplified nucleic acid levels were sufficient for analysis of Brucella gene expression patterns by RNA-sequencing, providing evidence of metabolic activity in both the short-term and the long-term samples. We developed a workflow for the use of sequence polymorphism analysis to confirm recovery of the inoculated strain in the recovered reads, and utilized clustering analysis to demonstrate a distinct transcriptional profile present in samples recovered in long-term infection. In this first look at B. melitensis gene expression patterns in vivo, the subset of Brucella genes that was highly upregulated in long-term as compared to short-term infection included genes linked to roles in murine infection, such as genes involved in proline utilization and signal transduction. Finally, we demonstrated the challenges of qPCR validation of samples with very low ratios of pathogen:host RNA, as is the case during in vivo brucellosis, and alternatively characterized intermediate products of the coincidence cloning reaction.ConclusionsOverall, this study provides the first example of recovery plus characterization of B. melitensis RNA from in vivo lymph node infection, and demonstrates that the coincidence cloning technique is a useful tool for characterizing in vivo transcriptional changes in Brucella species. Genes upregulated in long-term infection in this data set, including many genes not previously demonstrated to be virulence factors in mice or macrophage experiments, are candidates of future interest for potential roles in Brucella persistence in natural host systems.Electronic supplementary materialThe online version of this article (10.1186/s12867-018-0111-x) contains supplementary material, which is available to authorized users.

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“…The Ysrs are presumed Yersinia -specific sRNAs that were identified in an sRNA search in Y. pseudotuberculosis (Koo et al, 2011 ). A detailed list and the characteristics of these sRNAs are summarized in two recent reviews (Martínez-Chavarría and Vadyvaloo, 2015 ; Nuss et al, 2017b ) (Figure 2 , Table 1 ). Two aspects that are particularly striking are that (i) many sRNAs are directly regulated by the cAMP receptor protein (Crp) in response to growth phase and temperature, and that (ii) the majority of sRNAs are specific for Yersinia .…”

Section: Control By Regulatory Rnasmentioning

confidence: 99%

“…Much more is known about conserved sRNAs and their impact on pathogenicity of Yersinia . The most prominent influence on pathogenesis has been shown for the global carbon storage regulator system (Csr) (Heroven et al, 2012 ; Romeo et al, 2013 ; Vakulskas et al, 2015 ; Kusmierek and Dersch, 2017 ; Nuss et al, 2017b ). The Csr system of Yersinia consists of the small RNA-binding protein CsrA, which is highly conserved among many bacterial species, and the two non-coding sRNAs CsrB and CsrC.…”

Section: Control By Regulatory Rnasmentioning

confidence: 99%

Discovering RNA-Based Regulatory Systems for Yersinia Virulence

Knittel

Vollmer

Volk

et al. 2018

Front. Cell. Infect. Microbiol.

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The genus Yersinia includes three human pathogenic species, Yersinia pestis, the causative agent of the bubonic and pneumonic plague, and enteric pathogens Y. enterocolitica and Y. pseudotuberculosis that cause a number of gut-associated diseases. Over the past years a large repertoire of RNA-based regulatory systems has been discovered in these pathogens using different RNA-seq based approaches. Among them are several conserved or species-specific RNA-binding proteins, regulatory and sensory RNAs as well as various RNA-degrading enzymes. Many of them were shown to control the expression of important virulence-relevant factors and have a very strong impact on Yersinia virulence. The precise targets, the molecular mechanism and their role for Yersinia pathogenicity is only known for a small subset of identified genus- or species-specific RNA-based control elements. However, the ongoing development of new RNA-seq based methods and data analysis methods to investigate the synthesis, composition, translation, decay, and modification of RNAs in the bacterial cell will help us to generate a more comprehensive view of Yersinia RNA biology in the near future.

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RNA Regulators: Formidable Modulators of Yersinia Virulence

Cited by 12 publications

References 72 publications

Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes

Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes

Coincidence cloning recovery of Brucella melitensis RNA from goat tissues: advancing the in vivo analysis of pathogen gene expression in brucellosis

Discovering RNA-Based Regulatory Systems for Yersinia Virulence

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