Riboswitches for the alarmone ppGpp expand the collection of RNA-based signaling systems.
Riboswitches for the alarmone ppGpp expand the collection of RNA-based signaling systems.
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DOI:
10.1073/pnas.1720406115
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发表时间:
2018-06-05
影响因子:
11.1
通讯作者:
Breaker RR
中科院分区:
文献类型:
--
作者:
Sherlock ME;Sudarsan N;Breaker RR
Bacteria and other organisms make extensive use of signaling molecules that are derived from ribonucleotides or their derivatives. Previously, five riboswitch classes had been discovered that sense the four RNA-derived signaling molecules: c-di-GMP, c-di-AMP, c-AMP-GMP, and ZTP. We now report the discovery and biochemical validation of bacterial riboswitches for the widespread alarmone guanosine tetraphosphate (ppGpp), which signals metabolic and physiological adaptations to starvation. These findings expand the number of natural partnerships between riboswitches and ribonucleotide-like signaling molecules, and provide RNA-based sensors for detecting ppGpp production in cells. Riboswitches are noncoding portions of certain mRNAs that bind metabolite, coenzyme, signaling molecule, or inorganic ion ligands and regulate gene expression. Most known riboswitches sense derivatives of RNA monomers. This bias in ligand chemical composition is consistent with the hypothesis that widespread riboswitch classes first emerged during the RNA World, which is proposed to have existed before proteins were present. Here we report the discovery and biochemical validation of a natural riboswitch class that selectively binds guanosine tetraphosphate (ppGpp), a widespread signaling molecule and bacterial “alarmone” derived from the ribonucleotide GTP. Riboswitches for ppGpp are predicted to regulate genes involved in branched-chain amino acid biosynthesis and transport, as well as other gene classes that previously had not been implicated to be part of its signaling network. This newfound riboswitch–alarmone partnership supports the hypothesis that prominent RNA World signaling pathways have been retained by modern cells to control key biological processes.
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DOI:
10.1093/bioinformatics/btt509
发表时间:
2013-11-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
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通讯作者:
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影响因子:
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DOI:
10.1073/pnas.1419264112
发表时间:
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影响因子:
11.1
作者:
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通讯作者:
Breaker, Ronald R.
影响因子:
4.5
作者:
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通讯作者:
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影响因子:
16
作者:
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通讯作者:
Breaker RR