Riboswitch control of induction of aminoglycoside resistance acetyl and adenyl-transferases

He, Weizhi; Zhang, Xuhui; Zhang, Jun; Xu, Jin; Zhang, Jing; Sun, Wenxia; Jiang, Hengyi; Chen, Dongrong; Murchie, Alastair I. H.

doi:10.4161/rna.25757

Cited by 20 publications

(15 citation statements)

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“…Aminoglycosides, which bind specifically to 16S rRNA in the 30S ribosomal subunits to inhibit protein synthesis, are often used in combination with broad spectrum β -lactams to treat Gram-negative bacterial infections 6 , 7 , 8 . Resistance to aminoglycosides is most commonly caused by aminoglycoside modifying enzymes, including acetyltransferases, phosphotransferases and nucleotidyltransferases 9 , 10 . More recently, 16S rRNA methylases, ArmA, RmtA, RmtB, RmtC, RmtD, RmtE and NpmA have been reported among Enterobacteriaceae, Pseudomonas spp.…”

Section: Introductionmentioning

confidence: 99%

Genetic basis of high level aminoglycoside resistance in Acinetobacter baumannii from Beijing, China

Nie

Yuan

et al. 2014

Acta Pharmaceutica Sinica B

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The objective of this study was to investigate the genetic basis of high level aminoglycoside resistance in Acinetobacter baumannii clinical isolates from Beijing, China. 173 A. baumannii clinical isolates from hospitals in Beijing from 2006 to 2009 were first subjected to high level aminoglycoside resistance (HLAR, MIC to gentamicin and amikacin>512 µg/mL) phenotype selection by broth microdilution method. The strains were then subjected to genetic basis analysis by PCR detection of the aminoglycoside modifying enzyme genes (aac(3)-I, aac(3)-IIc, aac(6′)-Ib, aac(6′)-II, aph(4)-Ia, aph(3′)-I, aph(3′)-IIb, aph(3′)-IIIa, aph(3′)-VIa, aph(2″)-Ib, aph(2″)-Ic, aph(2″)-Id, ant(2″)-Ia, ant(3″)-I and ant(4′)-Ia) and the 16S rRNA methylase genes (armA, rmtB and rmtC). Correlation analysis between the presence of aminoglycoside resistance gene and HLAR phenotype were performed by SPSS. Totally 102 (58.96%) HLAR isolates were selected. The HLAR rates for year 2006, 2007, 2008 and 2009 were 52.63%, 65.22%, 51.11% and 70.83%, respectively. Five modifying enzyme genes (aac(3)-I, detection rate of 65.69%; aac(6′)-Ib, detection rate of 45.10%; aph(3′)-I, detection rate of 47.06%; aph(3′)-IIb, detection rate of 0.98%; ant(3″)-I, detection rate of 95.10%) and one methylase gene (armA, detection rate of 98.04%) were detected in the 102 A. baumannii with aac(3)-I+aac(6′)-Ib+ant(3″)-I+armA (detection rate of 25.49%), aac(3)-I+aph(3′)-I+ant(3″)-I+armA (detection rate of 21.57%) and ant(3″)-I+armA (detection rate of 12.75%) being the most prevalent gene profiles. The values of chi-square tests showed correlation of armA, ant(3″)-I, aac(3)-I, aph(3′)-I and aac(6′)-Ib with HLAR. armA had significant correlation (contingency coefficient 0.685) and good contingency with HLAR (kappa 0.940). The high rates of HLAR may cause a serious problem for combination therapy of aminoglycoside with β-lactams against A. baumannii infections. As armA was reported to be able to cause high level aminoglycoside resistance to most of the clinical important aminoglycosides (gentamicin, amikacin, tobramycin, etc), the function of aminoglycoside modifying enzyme gene(s) in A. baumannii carrying armA deserves further investigation.

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Section: Introductionmentioning

confidence: 99%

Genetic basis of high level aminoglycoside resistance in Acinetobacter baumannii from Beijing, China

Nie

Yuan

et al. 2014

Acta Pharmaceutica Sinica B

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“…The 5′ leader RNA, a riboswitch, of the aac/aad genes interacts with aminoglyco-sides and in turn activates the expression of the modifying enzymes. 38 , 40 , 67 In this regard, development of an antagonist, which prevents the binding of aminoglycosides to the leader sequence, may be useful to avoid the development of inducible resistance. Alternatively, modification of side chains of the next-generation aminoglycoside can facilitate their interaction with 30S ribosomal subunit rather than the 5′ leader sequence leading to transcription of degradative enzymes.…”

Section: Discussionmentioning

confidence: 99%

Potential and use of bacterial small RNAs to combat drug resistance: a systematic review

Chan¹,

Ho²,

Liu³

et al. 2017

IDR

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BackgroundOver the decades, new antibacterial agents have been developed in an attempt to combat drug resistance, but they remain unsuccessful. Recently, a novel class of bacterial gene expression regulators, bacterial small RNAs (sRNAs), has received increasing attention toward their involvement in antibiotic resistance. This systematic review aimed to discuss the potential of these small molecules as antibacterial drug targets.MethodsTwo investigators performed a comprehensive search of MEDLINE, EmBase, and ISI Web of Knowledge from inception to October 2016, without restriction on language. We included all in vitro and in vivo studies investigating the role of bacterial sRNA in antibiotic resistance. Risk of bias of the included studies was assessed by a modified guideline of Systematic Review Center for Laboratory Animal Experimentation (SYRCLE).ResultsInitial search yielded 432 articles. After exclusion of non-original articles, 20 were included in this review. Of these, all studies examined bacterial-type strains only. There were neither relevant in vivo nor clinical studies. The SYRCLE scores ranged from to 5 to 7, with an average of 5.9. This implies a moderate risk of bias. sRNAs influenced the antibiotics susceptibility through modulation of gene expression relevant to efflux pumps, cell wall synthesis, and membrane proteins.ConclusionPreclinical studies on bacterial-type strains suggest that modulation of sRNAs could enhance bacterial susceptibility to antibiotics. Further studies on clinical isolates and in vivo models are needed to elucidate the therapeutic value of sRNA modulation on treatment of multidrug-resistant bacterial infection.

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“…)—in a dose‐dependent manner, and to induce the expression of a β‐galactosidase reporter fusion by 2·5–3·2‐fold (He et al . ).…”

Section: Riboswitchesmentioning

confidence: 97%

Applications and limitations of regulatoryRNAelements in synthetic biology and biotechnology

et al. 2019

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Summary Synthetic biology requires the design and implementation of novel enzymes, genetic circuits or even entire cells, which can be controlled by the user. RNA‐based regulatory elements have many important functional properties in this regard, such as their modular nature and their ability to respond to specific external stimuli. These properties have led to the widespread exploration of their use as gene regulation devices in synthetic biology. In this review, we focus on two major types of RNA elements: riboswitches and RNA thermometers (RNATs). We describe their general structure and function, before discussing their potential uses in synthetic biology (e.g. in the production of biofuels and biodegradable plastics). We also discuss their limitations, and novel strategies to implement RNA‐based regulatory devices in biotechnological applications. We close with a description of some common model organisms used in synthetic biology, with a focus on the current applications and limitations of RNA‐based regulation.

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Riboswitch control of induction of aminoglycoside resistance acetyl and adenyl-transferases

Cited by 20 publications

References 68 publications

Genetic basis of high level aminoglycoside resistance in Acinetobacter baumannii from Beijing, China

Genetic basis of high level aminoglycoside resistance in Acinetobacter baumannii from Beijing, China

Potential and use of bacterial small RNAs to combat drug resistance: a systematic review

Applications and limitations of regulatoryRNAelements in synthetic biology and biotechnology

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