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Determinants of Target Prioritization and Regulatory Hierarchy for the Bacterial Small RNA Sgrs

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Determinants of Target Prioritization and Regulatory Hierarchy for the Bacterial Small RNA Sgrs Molecular Microbiology (2019) 112(4), 1199–1218 doi:10.1111/mmi.14355 First published online 6 August 2019 Determinants of target prioritization and regulatory hierarchy for the bacterial small RNA SgrS Maksym Bobrovskyy,1,† Muhammad S. Azam,1 of regulation of SgrS targets. The RNA chaperone Jane K. Frandsen,2,3,‡ Jichuan Zhang,4 Hfq uses distinct modes of binding to different SgrS Anustup Poddar,4 Xiangqian Ma,1 Tina M. Henkin,2 mRNA targets, which differentially influences posi- Taekjip Ha4,5 and Carin K. Vanderpool 1* tive and negative regulation. The RNA degradosome 1 Department of Microbiology, University of Illinois at plays a larger role in regulation of some SgrS targets Urbana-Champaign, 601 S. Goodwin Ave., Urbana, compared to others. Collectively, our results sug- IL 61801, USA. gest that sRNA selection of target mRNAs and regu- 2 Department of Microbiology and Center for RNA latory hierarchy are influenced by several molecular Biology, The Ohio State University, Columbus, features and that the combination of these features OH 43210, USA. precisely tunes the efficiency of regulation of multi- 3 Biochemistry Program, The Ohio State University, target sRNA regulons. Columbus, OH 43210, USA. 4 Department of Biophysics and Biophysical Chemistry, Johns Hopkins University, Baltimore, MD 21205, USA. Introduction 5 Howard Hughes Medical Institute, Baltimore, Bacteria live in diverse niches, often encountering rapidly MD 21205, USA. changing and stressful environments. Bacterial stress responses can mitigate the negative effects of stress on cell structure and function. Stress responses are usually coordinated by regulators, either RNAs or proteins, that Summary alter expression of a regulon comprised of multiple genes. Coordinated control of the regulon prepares the cell to Small RNA (sRNA) regulators promote efficient survive or adapt to the stress (Fang et al., 2016). Proteins responses to stress, but the mechanisms for prior- control expression of target regulons by binding to DNA itizing target mRNA regulation remain poorly under- sequences and modulating the frequency of transcription stood. This study examines mechanisms underlying initiation, whereas RNAs often modulate gene expression hierarchical regulation by the sRNA SgrS, found in posttranscriptionally. A prevalent type of RNA regulator enteric bacteria and produced under conditions of in bacteria is referred to simply as small RNA (sRNA). metabolic stress. SgrS posttranscriptionally coor- The sRNAs are often produced in response to a particu- dinates a nine-gene regulon to restore growth and lar stress, and regulate target mRNAs through base pair- homeostasis. An in vivo reporter system quanti- ing interactions that modify mRNA translation or stability fied SgrS-dependent regulation of target genes and (Georg and Hess, 2011; Storz et al., 2011). Hundreds of established that SgrS exhibits a clear target prefer- sRNAs have been identified in diverse bacteria (Zhang ence. Regulation of some targets is efficient even et al., 2003; Koo and Lathem, 2012; Carroll et al., 2016). at low SgrS levels, whereas higher SgrS concentra- While the majority of sRNAs have not been characterized, tions are required to regulate other targets. In vivo many studies suggest that sRNA regulatory networks are and in vitro analyses revealed that RNA structure and as extensive and complex as those controlled by proteins the number and position of base pairing sites rela- (Sharma et al., 2011; Salvail and Masse, 2012). tive to the start of translation impact the efficiency A large body of work has illuminated base pairing-de- Accepted 19 July, 2019. *For correspondence. E-mail cvanderp@ pendent molecular mechanisms of posttranscriptional illinois.edu; Tel. (+1) 217-333-7033; Fax (+1) 217-244-6697. Present regulation by sRNAs (Bobrovskyy and Vanderpool, 2013; † addresses: Department of Microbiology, The University of De Lay et al., 2013; Bobrovskyy et al., 2015; Papenfort and Chicago, 920 E. 58th St., Chicago, IL 60637, USA; ‡ Department of Biochemistry and Molecular Biology, Pennsylvania State University, Vanderpool, 2015; Kavita et al., 2018). The sRNA SgrS University Park, PA, USA. (sugar-phosphate stress sRNA) has been an important © 2019 John Wiley & Sons Ltd 1200 M. Bobrovskyy et al. model for discovery of both negative and positive mech- varies between negatively and positively regulated tar- anisms of target mRNA regulation. SgrS is induced in gets, and between stronger and weaker targets, imply- response to metabolic stress associated with disruption ing that Hfq plays a major role in determining efficiency of glycolytic flux and intracellular accumulation of sugar of sRNA-dependent regulation. Collectively, our results phosphates (also referred to as glucose-phosphate uphold the hypothesis that sRNAs regulate expression of stress) (Vanderpool and Gottesman, 2004; Vanderpool genes in their target regulons hierarchically, and that this and Gottesman, 2007; Richards et al., 2013). SgrS reg- is influenced by features of each sRNA–mRNA pair, dif- ulates at least nine genes and promotes recovery from ferent molecular mechanisms of regulation and the role of glucose-phosphate stress. SgrS-dependent repression accessory factors that precisely determine the regulatory of mRNAs encoding sugar transporters (ptsG, manXYZ) priority for each target. (Vanderpool and Gottesman, 2004; Rice and Vanderpool, 2011; Rice et al., 2012) reduces uptake of sugars to pre- vent further sugar-phosphate accumulation. Activation Results of a sugar phosphatase (yigL) mRNA promotes dephos- SgrS–target mRNA interactions have a range of phorylation and efflux of accumulated sugars (Papenfort predicted stabilities et al., 2013), and repression of other mRNAs is hypoth- esized to reroute metabolism to promote recovery from The thermodynamic stability of sRNA–target mRNA stress (Bobrovskyy and Vanderpool, 2016). Each target interactions likely influences the regulatory outcome. of SgrS is regulated by a distinct molecular mechanism. SgrS regulates genes posttranscriptionally by base pair- How different mechanisms of regulation yield effects of ing with target-binding sites on mRNAs (Bobrovskyy and variable magnitude with respect to mRNA stability and Vanderpool, 2016), which can be located in coding or translation is an open question. non-coding regions of the mRNA. The thermodynamic Temporally ordered and hierarchical patterns of gene stability of sRNA–mRNA duplexes for SgrS and its target regulation carried out by protein transcription factors have mRNAs ptsG, manX, purR, asd and yigL were predicted been characterized in many systems (Yu and Gerstein, in silico. The IntaRNA (Mann et al., 2017) hybridization 2006; Chevance and Hughes, 2008; Syed et al., 2009; energy value accounts for the energy required to unfold Tonner et al., 2015). These regulatory patterns allow cells each partner RNA to make binding sites accessible for to respond efficiently to environmental signals by prioritiz- base pairing, and the energy of hybridization of the part- ing induction or repression of products needed to respond ners (Table 1, Folded ΔG). We used full-length SgrS to those signals. Protein regulators can establish a hierar- (+1 to +227) for the sRNA input, and 5′ regions of target chy of regulation based on their affinities for binding sites mRNAs: ptsG (+1 to +180), manX (+1 to +180), purR (+1 in the operator regions of different target genes. As the to +300), asd (+1 to +180) and yigL (+1 to +258, where concentration of active regulator increases, genes are +1 is the processed end of the ’pldB-yigL transcript) sequentially regulated based on binding site affinity (Gao (Papenfort et al., 2013). SgrS interactions with ptsG and and Stock, 2015). There is growing evidence that sRNAs yigL mRNAs were predicted to be the most thermody- also regulate their target genes hierarchically (Levine et namically favorable (Table 1, Folded ΔG). Intermediate al., 2007; Feng et al., 2015). However, the mechanisms stabilities were predicted for SgrS base pairing with asdI involved in establishing and maintaining prioritized regu- (the primary SgrS-binding site on asd, near the transla- lation of sRNA targets are not known. tion initiation region (Bobrovskyy and Vanderpool, 2016)) We hypothesize that the temporal progression of tar- and purR. SgrS interactions with manX and asdII (the get regulation by SgrS is optimized to promote efficient secondary SgrS-binding site located in the coding region recovery from glucose-phosphate stress. To test this [Bobrovskyy and Vanderpool, 2016]) were predicted to hypothesis, we first defined the efficiency of SgrS regula- be the weakest (Table 1, Folded ΔG). tion of each target and found that SgrS indeed prioritizes Another algorithm, RNAhybrid (Kruger and regulation of some targets over others. We examined the Rehmsmeier, 2006), predicts the minimum free energy of factors that determine regulatory efficiency, including the SgrS hybridization with targets assuming that both RNA arrangement and strength of SgrS target-binding sites and partners are unfolded and accessible for intermolecular the roles of other factors like RNase E and Hfq. Detailed interactions. The predicted thermodynamic stabilities of characterization of a specific SgrS–mRNA target interac- SgrS–mRNA interactions predicted by this method were tion revealed cooperative binding of SgrS to two sites and (from highest to lowest): ptsG, asdI, yigL, purR, manX and a requirement for both binding sites for maximal SgrS- asdII (Table 1, Unfolded
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