1
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Frumkin I, Laub MT. Selection of a de novo gene that can promote survival of Escherichia coli by modulating protein homeostasis pathways. Nat Ecol Evol 2023; 7:2067-2079. [PMID: 37945946 PMCID: PMC10697842 DOI: 10.1038/s41559-023-02224-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 09/12/2023] [Indexed: 11/12/2023]
Abstract
Cellular novelty can emerge when non-functional loci become functional genes in a process termed de novo gene birth. But how proteins with random amino acid sequences beneficially integrate into existing cellular pathways remains poorly understood. We screened ~108 genes, generated from random nucleotide sequences and devoid of homology to natural genes, for their ability to rescue growth arrest of Escherichia coli cells producing the ribonuclease toxin MazF. We identified ~2,000 genes that could promote growth, probably by reducing transcription from the promoter driving toxin expression. Additionally, one random protein, named Random antitoxin of MazF (RamF), modulated protein homeostasis by interacting with chaperones, leading to MazF proteolysis and a consequent loss of its toxicity. Finally, we demonstrate that random proteins can improve during evolution by identifying beneficial mutations that turned RamF into a more efficient inhibitor. Our work provides a mechanistic basis for how de novo gene birth can produce functional proteins that effectively benefit cells evolving under stress.
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Affiliation(s)
- Idan Frumkin
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael T Laub
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Cambridge, MA, USA.
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2
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Lee KY, Lee BJ. Dynamics-Based Regulatory Switches of Type II Antitoxins: Insights into New Antimicrobial Discovery. Antibiotics (Basel) 2023; 12:antibiotics12040637. [PMID: 37106997 PMCID: PMC10135005 DOI: 10.3390/antibiotics12040637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 04/29/2023] Open
Abstract
Type II toxin-antitoxin (TA) modules are prevalent in prokaryotes and are involved in cell maintenance and survival under harsh environmental conditions, including nutrient deficiency, antibiotic treatment, and human immune responses. Typically, the type II TA system consists of two protein components: a toxin that inhibits an essential cellular process and an antitoxin that neutralizes its toxicity. Antitoxins of type II TA modules typically contain the structured DNA-binding domain responsible for TA transcription repression and an intrinsically disordered region (IDR) at the C-terminus that directly binds to and neutralizes the toxin. Recently accumulated data have suggested that the antitoxin's IDRs exhibit variable degrees of preexisting helical conformations that stabilize upon binding to the corresponding toxin or operator DNA and function as a central hub in regulatory protein interaction networks of the type II TA system. However, the biological and pathogenic functions of the antitoxin's IDRs have not been well discussed compared with those of IDRs from the eukaryotic proteome. Here, we focus on the current state of knowledge about the versatile roles of IDRs of type II antitoxins in TA regulation and provide insights into the discovery of new antibiotic candidates that induce toxin activation/reactivation and cell death by modulating the regulatory dynamics or allostery of the antitoxin.
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Affiliation(s)
- Ki-Young Lee
- College of Pharmacy and Institute of Pharmaceutical Sciences, CHA University, Pocheon-si 11160, Republic of Korea
| | - Bong-Jin Lee
- College of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea
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3
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Roca-Martinez J, Lazar T, Gavalda-Garcia J, Bickel D, Pancsa R, Dixit B, Tzavella K, Ramasamy P, Sanchez-Fornaris M, Grau I, Vranken WF. Challenges in describing the conformation and dynamics of proteins with ambiguous behavior. Front Mol Biosci 2022; 9:959956. [PMID: 35992270 PMCID: PMC9382080 DOI: 10.3389/fmolb.2022.959956] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Traditionally, our understanding of how proteins operate and how evolution shapes them is based on two main data sources: the overall protein fold and the protein amino acid sequence. However, a significant part of the proteome shows highly dynamic and/or structurally ambiguous behavior, which cannot be correctly represented by the traditional fixed set of static coordinates. Representing such protein behaviors remains challenging and necessarily involves a complex interpretation of conformational states, including probabilistic descriptions. Relating protein dynamics and multiple conformations to their function as well as their physiological context (e.g., post-translational modifications and subcellular localization), therefore, remains elusive for much of the proteome, with studies to investigate the effect of protein dynamics relying heavily on computational models. We here investigate the possibility of delineating three classes of protein conformational behavior: order, disorder, and ambiguity. These definitions are explored based on three different datasets, using interpretable machine learning from a set of features, from AlphaFold2 to sequence-based predictions, to understand the overlap and differences between these datasets. This forms the basis for a discussion on the current limitations in describing the behavior of dynamic and ambiguous proteins.
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Affiliation(s)
- Joel Roca-Martinez
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
| | - Tamas Lazar
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- VIB-VUB Center for Structural Biology, Brussels, Belgium
| | - Jose Gavalda-Garcia
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
| | - David Bickel
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
| | - Rita Pancsa
- Research Centre for Natural Sciences, Institute of Enzymology, Budapest, Hungary
| | - Bhawna Dixit
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
- IBiTech-Biommeda, Universiteit Gent, Gent, Belgium
| | - Konstantina Tzavella
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
| | - Pathmanaban Ramasamy
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
- VIB-UGent Center for Medical Biotechnology, Universiteit Gent, Gent, Belgium
| | - Maite Sanchez-Fornaris
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
- Department of Computer Sciences, University of Camagüey, Camagüey, Cuba
| | - Isel Grau
- Information Systems, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Wim F. Vranken
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels, Belgium
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4
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Zheng X, Liu W, Dai X, Zhu Y, Wang J, Zhu Y, Zheng H, Huang Y, Dong Z, Du W, Zhao F, Huang L. Extraordinary diversity of viruses in deep-sea sediments as revealed by metagenomics without prior virion separation. Environ Microbiol 2020; 23:728-743. [PMID: 32627268 DOI: 10.1111/1462-2920.15154] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 07/03/2020] [Indexed: 12/18/2022]
Abstract
Our current knowledge of the virosphere in deep-sea sediments remains rudimentary. Here we investigated viral diversity at both gene and genomic levels in deep-sea sediments of Southwest Indian Ocean. Analysis of 19 676 106 non-redundant genes from the metagenomic DNA sequences revealed a large number of unclassified viral groups in these samples. A total of 1106 high-confidence viral contigs were obtained after two runs of assemblies, and 217 of these contigs with sizes up to ~120 kb were shown to represent complete viral genomes. These contigs are clustered with no known viral genomes, and over 2/3 of the ORFs on the viral contigs encode no known functions. Furthermore, most of the complete viral contigs show limited similarity to known viral genomes in genome organization. Most of the classified viral contigs are derived from dsDNA viruses belonging to the order Caudovirales, including primarily members of the families Myoviridae, Podoviridae and Siphoviridae. Most of these viruses infect Proteobacteria and, less frequently, Planctomycetes, Firmicutes, Chloroflexi, etc. Auxiliary metabolic genes (AMGs), present in abundance on the viral contigs, appear to function in modulating the host ability to sense environmental gradients and community changes, and to uptake and metabolize nutrients.
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Affiliation(s)
- Xiaowei Zheng
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wang Liu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xin Dai
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yaxin Zhu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jinfeng Wang
- Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yongqiang Zhu
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, China
| | - Huajun Zheng
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, China
| | - Ying Huang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhiyang Dong
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wenbin Du
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.,Savaid Medical School, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Fangqing Zhao
- Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Li Huang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
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5
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Jurėnas D, Van Melderen L, Garcia-Pino A. Crystallization and X-ray analysis of all of the players in the autoregulation of the ataRT toxin-antitoxin system. Acta Crystallogr F Struct Biol Commun 2018; 74:391-401. [PMID: 29969102 PMCID: PMC6038448 DOI: 10.1107/s2053230x18007914] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 05/29/2018] [Indexed: 01/02/2023] Open
Abstract
The ataRT operon from enteropathogenic Escherichia coli encodes a toxin-antitoxin (TA) module with a recently discovered novel toxin activity. This new type II TA module targets translation initiation for cell-growth arrest. Virtually nothing is known regarding the molecular mechanisms of neutralization, toxin catalytic action or translation autoregulation. Here, the production, biochemical analysis and crystallization of the intrinsically disordered antitoxin AtaR, the toxin AtaT, the AtaR-AtaT complex and the complex of AtaR-AtaT with a double-stranded DNA fragment of the operator region of the promoter are reported. Because they contain large regions that are intrinsically disordered, TA antitoxins are notoriously difficult to crystallize. AtaR forms a homodimer in solution and crystallizes in space group P6122, with unit-cell parameters a = b = 56.3, c = 160.8 Å. The crystals are likely to contain an AtaR monomer in the asymmetric unit and diffracted to 3.8 Å resolution. The Y144F catalytic mutant of AtaT (AtaTY144F) bound to the cofactor acetyl coenzyme A (AcCoA) and the C-terminal neutralization domain of AtaR (AtaR44-86) were also crystallized. The crystals of the AtaTY144F-AcCoA complex diffracted to 2.5 Å resolution and the crystals of AtaR44-86 diffracted to 2.2 Å resolution. Analysis of these structures should reveal the full scope of the neutralization of the toxin AtaT by AtaR. The crystals belonged to space groups P6522 and P3121, with unit-cell parameters a = b = 58.1, c = 216.7 Å and a = b = 87.6, c = 125.5 Å, respectively. The AtaR-AtaT-DNA complex contains a 22 bp DNA duplex that was optimized to obtain high-resolution data based on the sequence of two inverted repeats detected in the operator region. It crystallizes in space group C2221, with unit-cell parameters a = 75.6, b = 87.9, c = 190.5 Å. These crystals diffracted to 3.5 Å resolution.
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Affiliation(s)
- Dukas Jurėnas
- Cellular and Molecular Microbiology, Université Libre de Bruxelles (ULB), Rue des Professeurs Jeener et Brachet 12, B-6041 Gosselies, Belgium
- Department of Biochemistry and Molecular Biology, Vilnius University Joint Life Sciences Center, Sauletekio Ave. 7, LT-10257 Vilnius, Lithuania
| | - Laurence Van Melderen
- Cellular and Molecular Microbiology, Université Libre de Bruxelles (ULB), Rue des Professeurs Jeener et Brachet 12, B-6041 Gosselies, Belgium
| | - Abel Garcia-Pino
- Cellular and Molecular Microbiology, Université Libre de Bruxelles (ULB), Rue des Professeurs Jeener et Brachet 12, B-6041 Gosselies, Belgium
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6
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Structural Determinants for Antitoxin Identity and Insulation of Cross Talk between Homologous Toxin-Antitoxin Systems. J Bacteriol 2016; 198:3287-3295. [PMID: 27672196 DOI: 10.1128/jb.00529-16] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Accepted: 09/20/2016] [Indexed: 01/10/2023] Open
Abstract
Toxin-antitoxin (TA) systems are ubiquitous in bacteria and archaea, where they play a pivotal role in the establishment and maintenance of dormancy. Under normal growth conditions, the antitoxin neutralizes the toxin. However, under conditions of stress, such as nutrient starvation or antibiotic treatment, cellular proteases degrade the antitoxin, and the toxin functions to arrest bacterial growth. We characterized the specificity determinants of the interactions between VapB antitoxins and VapC toxins from nontypeable Haemophilus influenzae (NTHi) in an effort to gain a better understanding of how antitoxins control toxin activity and bacterial persistence. We studied truncated and full-length antitoxins with single amino acid mutations in the toxin-binding domain. Coexpressing the toxin and antitoxin in Escherichia coli and measuring bacterial growth by dilution plating assayed the ability of the mutant antitoxins to neutralize the toxin. Our results identified two single amino acid residues (W48 and F52) in the C-terminal region of the VapB2 antitoxin necessary for its ability to neutralize its cognate VapC2 toxin. Additionally, we attempted to alter the specificity of VapB1 by making a mutation that would allow it to neutralize its noncognate toxin. A mutation in VapB1 to contain the tryptophan residue identified herein as important in the VapB2-VapC2 interaction resulted in a VapB1 mutant (the T47W mutant) that binds to and neutralizes both its cognate VapC1 and noncognate VapC2 toxins. This represents the first example of a single mutation causing relaxed specificity in a type II antitoxin. IMPORTANCE Toxin-antitoxin systems are of particular concern in pathogenic organisms, such as nontypeable Haemophilus influenzae, as they can elicit dormancy and persistence, leading to chronic infections and failure of antibiotic treatment. Despite the importance of the TA interaction, the specificity determinants for VapB-VapC complex formation remain uncharacterized. Thus, our understanding of how antitoxins control toxin-induced dormancy and bacterial persistence requires thorough investigation of antitoxin specificity for its cognate toxin. This study characterizes the crucial residues of the VapB2 antitoxin from NTHi necessary for its interaction with VapC2 and provides the first example of a single amino acid change altering the toxin specificity of an antitoxin.
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7
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Crystal Structure of the Escherichia coli Fic Toxin-Like Protein in Complex with Its Cognate Antitoxin. PLoS One 2016; 11:e0163654. [PMID: 27657533 PMCID: PMC5033356 DOI: 10.1371/journal.pone.0163654] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 09/12/2016] [Indexed: 12/29/2022] Open
Abstract
FIC domain proteins mediate post-translational modifications of target proteins, which typically results in their inactivation. Depending on the conservation of crucial active site residues, the FIC fold serves as structural scaffold for various enzymatic activities, mostly target adenylylation. The founding member of the vast Fic protein family, EcFicT, was identified in Escherichia coli some time ago. The G55R point mutant of EcFicT displays the "filamentation induced by cAMP" (Fic) phenotype at high 3',5'-cyclic adenosine monophosphate (cAMP) concentrations and elevated temperature, but the underlying molecular mechanism and any putative biochemical activity of EcFicT have remained unknown. EcFicT belongs to class I Fic toxin proteins that are encoded together with a small inhibitory protein (antitoxin), named EcFicA in E. coli. Here, we report the crystal structures of two mutant EcFicT/EcFicA complexes (EcFicTG55RA and EcFicTAE28G) both showing close resemblance with the structure of the AMP-transferase VbhT from Bartonella schoenbuchensis in complex with its cognate antitoxin VbhA. However, crucial differences in the active site of EcFicT compared to VbhT and other AMP-transferases rationalize the lack of evidence for adenylylation activity. Comprehensive bioinformatic analysis suggests that EcFicT has evolved from canonical AMP-transferases and has acquired a conserved binding site for a yet to be discovered novel substrate. The G55R mutation has no effect on structure or thermal stability of EcFicT, such that the molecular basis for its associated Fic phenotype remains elusive. We anticipate that this structure will inspire further bioinformatic and experimental analyses in order to characterize the enzymatic activity of EcFicT and help revealing its physiological role.
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ATP and autophosphorylation driven conformational changes of HipA kinase revealed by ion mobility and crosslinking mass spectrometry. Anal Bioanal Chem 2016; 408:5925-5933. [PMID: 27325463 DOI: 10.1007/s00216-016-9709-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Revised: 06/04/2016] [Accepted: 06/09/2016] [Indexed: 01/26/2023]
Abstract
Toxin-antitoxin systems are genetic modules involved in a broad range of bacterial cellular processes including persistence, multidrug resistance and tolerance, biofilm formation, and pathogenesis. In type II toxin-antitoxin systems, both the toxin and antitoxin are proteins. In the prototypic Escherichia coli HipA-HipB module, the antitoxin HipB forms a complex with the protein kinase HipA and sequesters it in the nucleoid. HipA is then no longer able to phosphorylate glutamyl-tRNA-synthetase and this prevents the initiation of the forthcoming stringent response. Here we investigated the assembly of the Shewanella oneidensis MR-1 HipA-HipB complex using native electrospray ion mobility-mass spectrometry and chemical crosslinking combined with mass spectrometry. We revealed that the HipA autophosphorylation was accompanied by a large conformational change, and confirmed structural evidence that S. oneidensis MR-1 HipA-HipB assembly was distinct from the prototypic E. coli HipA-HipB complex. Graphical abstract Ion mobility mass spectrometry shows a two phase transition from unstructured HipA to a compact folded phosphorylated protein.
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9
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Garcia-Pino A, De Gieter S, Talavera A, De Greve H, Efremov RG, Loris R. An intrinsically disordered entropic switch determines allostery in Phd-Doc regulation. Nat Chem Biol 2016; 12:490-6. [PMID: 27159580 DOI: 10.1038/nchembio.2078] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Accepted: 03/11/2016] [Indexed: 12/31/2022]
Abstract
Conditional cooperativity is a common mechanism involved in transcriptional regulation of prokaryotic type II toxin-antitoxin operons and is intricately related to bacterial persistence. It allows the toxin component of a toxin-antitoxin module to act as a co-repressor at low doses of toxin as compared to antitoxin. When toxin level exceeds a certain threshold, however, the toxin becomes a de-repressor. Most antitoxins contain an intrinsically disordered region (IDR) that typically is involved in toxin neutralization and repressor complex formation. To address how the antitoxin IDR is involved in transcription regulation, we studied the phd-doc operon from bacteriophage P1. We provide evidence that the IDR of Phd provides an entropic barrier precluding full operon repression in the absence of Doc. Binding of Doc results in a cooperativity switch and consequent strong operon repression, enabling context-specific modulation of the regulatory process. Variations of this theme are likely to be a common mechanism in the autoregulation of bacterial operons that involve intrinsically disordered regions.
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Affiliation(s)
- Abel Garcia-Pino
- Structural Biology Brussels, Department of Biotechnology, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,Biologie Structurale et Biophysique, Université Libre de Bruxelles (ULB), Gosselies, Belgium
| | - Steven De Gieter
- Structural Biology Brussels, Department of Biotechnology, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,Structural Biology Research Center, VIB, Brussels, Belgium
| | - Ariel Talavera
- Structural Biology Brussels, Department of Biotechnology, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,Structural Biology Research Center, VIB, Brussels, Belgium
| | - Henri De Greve
- Structural Biology Brussels, Department of Biotechnology, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,Structural Biology Research Center, VIB, Brussels, Belgium
| | - Rouslan G Efremov
- Structural Biology Brussels, Department of Biotechnology, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,Structural Biology Research Center, VIB, Brussels, Belgium
| | - Remy Loris
- Structural Biology Brussels, Department of Biotechnology, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,Structural Biology Research Center, VIB, Brussels, Belgium
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