1
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Purtov YA, Ozoline ON. Neuromodulators as Interdomain Signaling Molecules Capable of Occupying Effector Binding Sites in Bacterial Transcription Factors. Int J Mol Sci 2023; 24:15863. [PMID: 37958845 PMCID: PMC10647483 DOI: 10.3390/ijms242115863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/29/2023] [Accepted: 10/30/2023] [Indexed: 11/15/2023] Open
Abstract
Hormones and neurotransmitters are important components of inter-kingdom signaling systems that ensure the coexistence of eukaryotes with their microbial community. Their ability to affect bacterial physiology, metabolism, and gene expression was evidenced by various experimental approaches, but direct penetration into bacteria has only recently been reported. This opened the possibility of considering neuromodulators as potential effectors of bacterial ligand-dependent regulatory proteins. Here, we assessed the validity of this assumption for the neurotransmitters epinephrine, dopamine, and norepinephrine and two hormones (melatonin and serotonin). Using flexible molecular docking for transcription factors with ligand-dependent activity, we assessed the ability of neuromodulators to occupy their effector binding sites. For many transcription factors, including the global regulator of carbohydrate metabolism, CRP, and the key regulator of lactose assimilation, LacI, this ability was predicted based on the analysis of several 3D models. By occupying the ligand binding site, neuromodulators can sterically hinder the interaction of the target proteins with the natural effectors or even replace them. The data obtained suggest that the direct modulation of the activity of at least some bacterial transcriptional factors by neuromodulators is possible. Therefore, the natural hormonal background may be a factor that preadapts bacteria to the habitat through direct perception of host signaling molecules.
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Affiliation(s)
- Yuri A. Purtov
- Department of Functional Genomics of Prokaryotes, Institute of Cell Biophysics of the Russian Academy of Sciences, Federal Research Center Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, Pushchino 142290, Russia
| | - Olga N. Ozoline
- Department of Functional Genomics of Prokaryotes, Institute of Cell Biophysics of the Russian Academy of Sciences, Federal Research Center Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, Pushchino 142290, Russia
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2
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Waters EV, Tucker LA, Ahmed JK, Wain J, Langridge GC. Impact of Salmonella genome rearrangement on gene expression. Evol Lett 2022; 6:426-437. [PMID: 36579163 PMCID: PMC9783417 DOI: 10.1002/evl3.305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/03/2022] [Accepted: 11/07/2022] [Indexed: 11/20/2022] Open
Abstract
In addition to nucleotide variation, many bacteria also undergo changes at a much larger scale via rearrangement of their genome structure (GS) around long repeat sequences. These rearrangements result in genome fragments shifting position and/or orientation in the genome without necessarily affecting the underlying nucleotide sequence. To date, scalable techniques have not been applied to GS identification, so it remains unclear how extensive this variation is and the extent of its impact upon gene expression. However, the emergence of multiplexed, long-read sequencing overcomes the scale problem, as reads of several thousand bases are routinely produced that can span long repeat sequences to identify the flanking chromosomal DNA, allowing GS identification. Genome rearrangements were generated in Salmonella enterica serovar Typhi through long-term culture at ambient temperature. Colonies with rearrangements were identified via long-range PCR and subjected to long-read nanopore sequencing to confirm genome variation. Four rearrangements were investigated for differential gene expression using transcriptomics. All isolates with changes in genome arrangement relative to the parent strain were accompanied by changes in gene expression. Rearrangements with similar fragment movements demonstrated similar changes in gene expression. The most extreme rearrangement caused a large imbalance between the origin and terminus of replication and was associated with differential gene expression as a factor of distance moved toward or away from the origin of replication. Genome structure variation may provide a mechanism through which bacteria can quickly adapt to new environments and warrants routine assessment alongside traditional nucleotide-level measures of variation.
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Affiliation(s)
- Emma V. Waters
- Microbes in the Food ChainQuadram Institute BioscienceNorwichNR4 7UQUnited Kingdom
| | - Liam A. Tucker
- Microbes in the Food ChainQuadram Institute BioscienceNorwichNR4 7UQUnited Kingdom
| | - Jana K. Ahmed
- The Wellcome Trust Sanger InstituteCambridgeCB10 1SAUnited Kingdom
| | - John Wain
- Microbes in the Food ChainQuadram Institute BioscienceNorwichNR4 7UQUnited Kingdom,Norwich Medical SchoolUniversity of East AngliaNorwichNR4 7TJUnited Kingdom
| | - Gemma C. Langridge
- Microbes in the Food ChainQuadram Institute BioscienceNorwichNR4 7UQUnited Kingdom
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3
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Buchanan CJ, Gaunt B, Harrison PJ, Yang Y, Liu J, Khan A, Giltrap AM, Le Bas A, Ward PN, Gupta K, Dumoux M, Tan TK, Schimaski L, Daga S, Picchiotti N, Baldassarri M, Benetti E, Fallerini C, Fava F, Giliberti A, Koukos PI, Davy MJ, Lakshminarayanan A, Xue X, Papadakis G, Deimel LP, Casablancas-Antràs V, Claridge TDW, Bonvin AMJJ, Sattentau QJ, Furini S, Gori M, Huo J, Owens RJ, Schaffitzel C, Berger I, Renieri A, Naismith JH, Baldwin AJ, Davis BG. Pathogen-sugar interactions revealed by universal saturation transfer analysis. Science 2022; 377:eabm3125. [PMID: 35737812 DOI: 10.1126/science.abm3125] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an "end-on" manner. uSTA-guided modeling and a high-resolution cryo-electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis.
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Affiliation(s)
- Charles J Buchanan
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK.,Kavli Institute of Nanoscience Discovery, University of Oxford, Oxford OX1 3QU, UK
| | - Ben Gaunt
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK
| | - Peter J Harrison
- Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK.,Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire, UK
| | - Yun Yang
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK
| | - Jiwei Liu
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK
| | - Aziz Khan
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK
| | - Andrew M Giltrap
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK
| | - Audrey Le Bas
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK
| | - Philip N Ward
- Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK
| | - Kapil Gupta
- Max Planck Bristol Centre for Minimal Biology, University of Bristol, Bristol, UK
| | - Maud Dumoux
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK
| | - Tiong Kit Tan
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Lisa Schimaski
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Sergio Daga
- Medical Genetics, University of Siena, Siena, Italy.,Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Nicola Picchiotti
- Department of Information Engineering and Mathematics, University of Siena, Siena, Italy.,Department of Mathematics, University of Pavia, Pavia, Italy
| | - Margherita Baldassarri
- Medical Genetics, University of Siena, Siena, Italy.,Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Elisa Benetti
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Chiara Fallerini
- Medical Genetics, University of Siena, Siena, Italy.,Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Francesca Fava
- Medical Genetics, University of Siena, Siena, Italy.,Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy.,Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Annarita Giliberti
- Medical Genetics, University of Siena, Siena, Italy.,Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Panagiotis I Koukos
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Matthew J Davy
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK
| | - Abirami Lakshminarayanan
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK
| | - Xiaochao Xue
- Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK.,Sir William Dunn School of Pathology, Oxford, UK
| | | | | | - Virgínia Casablancas-Antràs
- Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK.,Kavli Institute of Nanoscience Discovery, University of Oxford, Oxford OX1 3QU, UK
| | | | - Alexandre M J J Bonvin
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | | | - Simone Furini
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Marco Gori
- Department of Information Engineering and Mathematics, University of Siena, Siena, Italy.,Maasai, I3S CNRS, Université Côte d'Azur, Nice, France
| | - Jiandong Huo
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK
| | - Raymond J Owens
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK
| | - Christiane Schaffitzel
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Imre Berger
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Alessandra Renieri
- Medical Genetics, University of Siena, Siena, Italy.,Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy.,Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | | | - James H Naismith
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Headington, Oxford OX3 7BN, UK
| | - Andrew J Baldwin
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK.,Kavli Institute of Nanoscience Discovery, University of Oxford, Oxford OX1 3QU, UK
| | - Benjamin G Davis
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Oxford OX11 0FA, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK.,Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
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4
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Neetu N, Katiki M, Mahto JK, Sharma M, Narayanan A, Maity S, Tomar S, Ambatipudi K, Sharma AK, Yernool D, Kumar P. Deciphering the enigma of missing DNA binding domain of LacI family transcription factors. Arch Biochem Biophys 2021; 713:109060. [PMID: 34666048 DOI: 10.1016/j.abb.2021.109060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 10/09/2021] [Accepted: 10/11/2021] [Indexed: 11/19/2022]
Abstract
Catabolite repressor activator (Cra) is a member of the LacI family transcriptional regulator distributed across a wide range of bacteria and regulates the carbon metabolism and virulence gene expression. In numerous studies to crystallize the apo form of the LacI family transcription factor, the N-terminal domain (NTD), which functions as a DNA-binding domain, has been enigmatically missing from the final resolved structures. It was speculated that the NTD is disordered or unstable and gets cleaved during crystallization. Here, we have determined the crystal structure of Cra from Escherichia coli (EcCra). The structure revealed a well-defined electron density for the C-terminal domain (CTD). However, electron density was missing for the first 56 amino acids (NTD). Our data reveal for the first time that EcCra undergoes a spontaneous cleavage at the conserved Asn 50 (N50) site, which separates the N-terminal DNA binding domain from the C-terminal effector molecule binding domain. With the site-directed mutagenesis, we confirm the involvement of residue N50 in the spontaneous cleavage phenomenon. Furthermore, the Isothermal titration calorimetry (ITC) assay of the EcCra-NTD with DNA showed EcCra-NTD is in a functional conformation state and retains its DNA binding activity.
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Affiliation(s)
- Neetu Neetu
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Madhusudhanarao Katiki
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Jai Krishna Mahto
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Monica Sharma
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Anoop Narayanan
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Sudipa Maity
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Shailly Tomar
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Kiran Ambatipudi
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Ashwani Kumar Sharma
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
| | - Dinesh Yernool
- Department of Biological Sciences, Purdue University, West Lafayette, IN, 47906, USA
| | - Pravindra Kumar
- Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
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5
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Matilla MA, Velando F, Martín-Mora D, Monteagudo-Cascales E, Krell T. A catalogue of signal molecules that interact with sensor kinases, chemoreceptors and transcriptional regulators. FEMS Microbiol Rev 2021; 46:6356564. [PMID: 34424339 DOI: 10.1093/femsre/fuab043] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/10/2021] [Indexed: 12/12/2022] Open
Abstract
Bacteria have evolved many different signal transduction systems that sense signals and generate a variety of responses. Generally, most abundant are transcriptional regulators, sensor histidine kinases and chemoreceptors. Typically, these systems recognize their signal molecules with dedicated ligand-binding domains (LBDs), which, in turn, generate a molecular stimulus that modulates the activity of the output module. There are an enormous number of different LBDs that recognize a similarly diverse set of signals. To give a global perspective of the signals that interact with transcriptional regulators, sensor kinases and chemoreceptors, we manually retrieved information on the protein-ligand interaction from about 1,200 publications and 3D structures. The resulting 811 proteins were classified according to the Pfam family into 127 groups. These data permit a delineation of the signal profiles of individual LBD families as well as distinguishing between families that recognize signals in a promiscuous manner and those that possess a well-defined ligand range. A major bottleneck in the field is the fact that the signal input of many signaling systems is unknown. The signal repertoire reported here will help the scientific community design experimental strategies to identify the signaling molecules for uncharacterised sensor proteins.
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Affiliation(s)
- Miguel A Matilla
- Department of Environmental Protection, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, Prof. Albareda 1, 18008 Granada, Spain
| | - Félix Velando
- Department of Environmental Protection, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, Prof. Albareda 1, 18008 Granada, Spain
| | - David Martín-Mora
- Department of Environmental Protection, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, Prof. Albareda 1, 18008 Granada, Spain
| | - Elizabet Monteagudo-Cascales
- Department of Environmental Protection, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, Prof. Albareda 1, 18008 Granada, Spain
| | - Tino Krell
- Department of Environmental Protection, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, Prof. Albareda 1, 18008 Granada, Spain
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6
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Sousa FL, Parente DJ, Hessman JA, Chazelle A, Teichmann SA, Swint-Kruse L. Data on publications, structural analyses, and queries used to build and utilize the AlloRep database. Data Brief 2016; 8:948-57. [PMID: 27508249 PMCID: PMC4961497 DOI: 10.1016/j.dib.2016.07.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Revised: 06/22/2016] [Accepted: 07/04/2016] [Indexed: 01/08/2023] Open
Abstract
The AlloRep database (www.AlloRep.org) (Sousa et al., 2016) [1] compiles extensive sequence, mutagenesis, and structural information for the LacI/GalR family of transcription regulators. Sequence alignments are presented for >3000 proteins in 45 paralog subfamilies and as a subsampled alignment of the whole family. Phenotypic and biochemical data on almost 6000 mutants have been compiled from an exhaustive search of the literature; citations for these data are included herein. These data include information about oligomerization state, stability, DNA binding and allosteric regulation. Protein structural data for 65 proteins are presented as easily-accessible, residue-contact networks. Finally, this article includes example queries to enable the use of the AlloRep database. See the related article, “AlloRep: a repository of sequence, structural and mutagenesis data for the LacI/GalR transcription regulators” (Sousa et al., 2016) [1].
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Affiliation(s)
- Filipa L Sousa
- Institute of Molecular Evolution, Heinrich-Heine Universität Düsseldorf, Universitätstrasse 1, 40225 Düsseldorf, Germany
| | - Daniel J Parente
- The Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Jacob A Hessman
- The Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Allen Chazelle
- The Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Sarah A Teichmann
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Liskin Swint-Kruse
- The Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS 66160, USA
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7
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Engineering Synthetic Multistress Tolerance in Escherichia coli by Using a Deinococcal Response Regulator, DR1558. Appl Environ Microbiol 2015; 82:1154-1166. [PMID: 26655758 DOI: 10.1128/aem.03371-15] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 11/20/2015] [Indexed: 12/15/2022] Open
Abstract
Cellular robustness is an important trait for industrial microbes, because the microbial strains are exposed to a multitude of different stresses during industrial processes, such as fermentation. Thus, engineering robustness in an organism in order to push the strains toward maximizing yield has become a significant topic of research. We introduced the deinococcal response regulator DR1558 into Escherichia coli (strain Ec-1558), thereby conferring tolerance to hydrogen peroxide (H2O2). The reactive oxygen species (ROS) level in strain Ec-1558 was reduced due to the increased KatE catalase activity. Among four regulators of the oxidative-stress response, OxyR, RpoS, SoxS, and Fur, we found that the expression of rpoS increased in Ec-1558, and we confirmed this increase by Western blot analysis. Electrophoretic mobility shift assays showed that DR1558 bound to the rpoS promoter. Because the alternative sigma factor RpoS regulates various stress resistance-related genes, we performed stress survival analysis using an rpoS mutant strain. Ec-1558 was able to tolerate a low pH, a high temperature, and high NaCl concentrations in addition to H2O2, and the multistress tolerance phenotype disappeared in the absence of rpoS. Microarray analysis clearly showed that a variety of stress-responsive genes that are directly or indirectly controlled by RpoS were upregulated in strain Ec-1558. These findings, taken together, indicate that the multistress tolerance conferred by DR1558 is likely routed through RpoS. In the present study, we propose a novel strategy of employing an exogenous response regulator from polyextremophiles for strain improvement.
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8
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Parente DJ, Ray JCJ, Swint-Kruse L. Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores. Proteins 2015; 83:2293-306. [PMID: 26503808 DOI: 10.1002/prot.24948] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Revised: 09/21/2015] [Accepted: 10/14/2015] [Indexed: 12/21/2022]
Abstract
As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions.
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Affiliation(s)
- Daniel J Parente
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, Kansas, 66160
| | - J Christian J Ray
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, 66047
| | - Liskin Swint-Kruse
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, Kansas, 66160
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9
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Peroza EA, Ewald JC, Parakkal G, Skotheim JM, Zamboni N. A genetically encoded Förster resonance energy transfer sensor for monitoring in vivo trehalose-6-phosphate dynamics. Anal Biochem 2015; 474:1-7. [PMID: 25582303 DOI: 10.1016/j.ab.2014.12.019] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 12/22/2014] [Accepted: 12/29/2014] [Indexed: 11/18/2022]
Abstract
Trehalose-6-phosphate is a pivotal regulator of sugar metabolism, growth, and osmotic equilibrium in bacteria, yeasts, and plants. To directly visualize the intracellular levels of intracellular trehalose-6-phosphate, we developed a series of specific Förster resonance energy transfer (FRET) sensors for in vivo microscopy. We demonstrated real-time monitoring of regulation in the trehalose pathway of Escherichia coli. In Saccharomyces cerevisiae, we could show that the concentration of free trehalose-6-phosphate during growth on glucose is in a range sufficient for inhibition of hexokinase. These findings support the hypothesis of trehalose-6-phosphate as the effector of a negative feedback system, similar to the inhibition of hexokinase by glucose-6-phosphate in mammalian cells and controlling glycolytic flux.
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Affiliation(s)
- Estevão A Peroza
- Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - Jennifer C Ewald
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Geetha Parakkal
- Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - Jan M Skotheim
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Nicola Zamboni
- Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
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10
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Smart OS, Bricogne G. Achieving High Quality Ligand Chemistry in Protein-Ligand Crystal Structures for Drug Design. MULTIFACETED ROLES OF CRYSTALLOGRAPHY IN MODERN DRUG DISCOVERY 2015. [DOI: 10.1007/978-94-017-9719-1_13] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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11
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Ketterer S, Hövermann D, Guebeli RJ, Bartels-Burgahn F, Riewe D, Altmann T, Zurbriggen MD, Junker B, Weber W, Meier M. Transcription factor sensor system for parallel quantification of metabolites on-chip. Anal Chem 2014; 86:12152-8. [PMID: 25479036 DOI: 10.1021/ac503269m] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Steadily growing demands for identification and quantification of cellular metabolites in higher throughput have brought a need for new analytical technologies. Here, we developed a synthetic biological sensor system for quantifying metabolites from biological cell samples. For this, bacterial transcription factors were exploited, which bind to or dissociate from regulatory DNA elements in response to physiological changes in the cellular metabolite concentration range. Representatively, the bacterial pyruvate dehydrogenase (PdhR), trehalose (TreR), and l-arginine (ArgR) repressor proteins were functionalized to detect pyruvate, trehalose-6-phosphate (T6P), and arginine concentration in solution. For each transcription factor the mutual binding behavior between metabolite and DNA, their working range, and othogonality were determined. High-throughput, parallel processing, and automation were achieved through integration of the metabolic sensor system on a microfluidic large-scale integration (mLSI) chip platform. To demonstrate the functionality of the integrated metabolic sensor system, we measured diurnal concentration changes of pyruvate and the plant signaling molecule T6P within cell etxracts of Arabidopsis thaliana rosettes. The transcription factor sensor system is of generic nature and extendable on the microfluidic chip.
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Affiliation(s)
- Simon Ketterer
- Microfluidic and Biological Engineering, Department of Microsystems Engineering, University of Freiburg , Georges-Koehler-Allee 103, 79110 Freiburg, Germany
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12
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Enzymatic and regulatory properties of the trehalose-6-phosphate synthase from the thermoacidophilic archaeon Thermoplasma acidophilum. Biochimie 2014; 101:215-20. [PMID: 24508535 DOI: 10.1016/j.biochi.2014.01.018] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Accepted: 01/27/2014] [Indexed: 11/22/2022]
Abstract
Trehalose-6-phosphate synthase plays an important role in trehalose metabolism. It catalyzes the transfer of glucose from UDP-glucose (UDPG) to glucose 6-phosphate to produce trehalose-6-phosphate. Herein we describe the characterization of a trehalose-6-phosphate synthase from the thermoacidophilic archaeon Thermoplasma acidophilum. The dimeric enzyme could utilize UDPG, ADP-Glucose (ADPG) and GDP-Glucose (GDPG) as glycosyl donors and various phosphorylated monosaccharides as glycosyl acceptors. The optimal temperature and pH were found to be 60 °C and pH 6, and the enzyme exhibited notable pH and thermal stability. The enzymatic activity could be stimulated by divalent metal ions and polyanions heparin and chondroitin sulfate. Moreover, the protein was considerably resistant to additives ethanol, EDTA, urea, DTT, SDS, β-mercaptoethanol, methanol, isopropanol and n-butanol. Molecular modeling and mutagenesis analysis revealed that the N-loop region was important for the catalytic efficiency of the enzyme, indicating different roles of N-loop sequences in different trehalose-6-phosphate synthases.
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13
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Parente DJ, Swint-Kruse L. Multiple co-evolutionary networks are supported by the common tertiary scaffold of the LacI/GalR proteins. PLoS One 2013; 8:e84398. [PMID: 24391951 PMCID: PMC3877293 DOI: 10.1371/journal.pone.0084398] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 11/15/2013] [Indexed: 11/18/2022] Open
Abstract
Protein families might evolve paralogous functions on their common tertiary scaffold in two ways. First, the locations of functionally-important sites might be "hard-wired" into the structure, with novel functions evolved by altering the amino acid (e.g. Ala vs Ser) at these positions. Alternatively, the tertiary scaffold might be adaptable, accommodating a unique set of functionally important sites for each paralogous function. To discriminate between these possibilities, we compared the set of functionally important sites in the six largest paralogous subfamilies of the LacI/GalR transcription repressor family. LacI/GalR paralogs share a common tertiary structure, but have low sequence identity (≤ 30%), and regulate a variety of metabolic processes. Functionally important positions were identified by conservation and co-evolutionary sequence analyses. Results showed that conserved positions use a mixture of the "hard-wired" and "accommodating" scaffold frameworks, but that the co-evolution networks were highly dissimilar between any pair of subfamilies. Therefore, the tertiary structure can accommodate multiple networks of functionally important positions. This possibility should be included when designing and interpreting sequence analyses of other protein families. Software implementing conservation and co-evolution analyses is available at https://sourceforge.net/projects/coevolutils/.
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Affiliation(s)
- Daniel J. Parente
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, Kansas, United States of America
| | - Liskin Swint-Kruse
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, Kansas, United States of America
- * E-mail:
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14
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Vandesteene L, López-Galvis L, Vanneste K, Feil R, Maere S, Lammens W, Rolland F, Lunn JE, Avonce N, Beeckman T, Van Dijck P. Expansive evolution of the trehalose-6-phosphate phosphatase gene family in Arabidopsis. PLANT PHYSIOLOGY 2012; 160:884-96. [PMID: 22855938 PMCID: PMC3461562 DOI: 10.1104/pp.112.201400] [Citation(s) in RCA: 97] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2012] [Accepted: 07/30/2012] [Indexed: 05/18/2023]
Abstract
Trehalose is a nonreducing sugar used as a reserve carbohydrate and stress protectant in a variety of organisms. While higher plants typically do not accumulate high levels of trehalose, they encode large families of putative trehalose biosynthesis genes. Trehalose biosynthesis in plants involves a two-step reaction in which trehalose-6-phosphate (T6P) is synthesized from UDP-glucose and glucose-6-phosphate (catalyzed by T6P synthase [TPS]), and subsequently dephosphorylated to produce the disaccharide trehalose (catalyzed by T6P phosphatase [TPP]). In Arabidopsis (Arabidopsis thaliana), 11 genes encode proteins with both TPS- and TPP-like domains but only one of these (AtTPS1) appears to be an active (TPS) enzyme. In addition, plants contain a large family of smaller proteins with a conserved TPP domain. Here, we present an in-depth analysis of the 10 TPP genes and gene products in Arabidopsis (TPPA-TPPJ). Collinearity analysis revealed that all of these genes originate from whole-genome duplication events. Heterologous expression in yeast (Saccharomyces cerevisiae) showed that all encode active TPP enzymes with an essential role for some conserved residues in the catalytic domain. These results suggest that the TPP genes function in the regulation of T6P levels, with T6P emerging as a novel key regulator of growth and development in higher plants. Extensive gene expression analyses using a complete set of promoter-β-glucuronidase/green fluorescent protein reporter lines further uncovered cell- and tissue-specific expression patterns, conferring spatiotemporal control of trehalose metabolism. Consistently, phenotypic characterization of knockdown and overexpression lines of a single TPP, AtTPPG, points to unique properties of individual TPPs in Arabidopsis, and underlines the intimate connection between trehalose metabolism and abscisic acid signaling.
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Affiliation(s)
| | | | - Kevin Vanneste
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Regina Feil
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Steven Maere
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Willem Lammens
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Filip Rolland
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - John E. Lunn
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Nelson Avonce
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Tom Beeckman
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
| | - Patrick Van Dijck
- Department of Molecular Microbiology, VIB, Leuven, Belgium (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Cell Biology (L.V., L.L.-G., N.A., P.V.D.), Laboratory of Molecular Plant Physiology (W.L.), and Laboratory of Molecular Plant Biology-Plant Metabolic Signaling (F.R.), Institute of Botany and Microbiology, KU Leuven, B–3001 Leuven, Belgium; Department of Plant Systems Biology, VIB, Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Department of Plant Biotechnology and Bioinformatics, Ghent University, B–9052 Ghent, Belgium (L.L.-G., K.V., S.M., T.B.); Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany (R.F., J.E.L.)
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15
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Hädrich N, Gibon Y, Schudoma C, Altmann T, Lunn JE, Stitt M. Use of TILLING and robotised enzyme assays to generate an allelic series of Arabidopsis thaliana mutants with altered ADP-glucose pyrophosphorylase activity. JOURNAL OF PLANT PHYSIOLOGY 2011; 168:1395-405. [PMID: 21345514 DOI: 10.1016/j.jplph.2011.01.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2010] [Revised: 01/25/2011] [Accepted: 01/26/2011] [Indexed: 05/25/2023]
Abstract
ADP-glucose pyrophosphorylase (AGPase) catalyses the synthesis of ADP-glucose, and is a highly regulated enzyme in the pathway of starch synthesis. In Arabidopsis thaliana, the enzyme is a heterotetramer, containing two small subunits encoded by the APS1 gene and two large subunits encoded by the APL1-4 genes. TILLING (Targeting Induced Local Lesions IN Genomes) of a chemically mutagenised population of A. thaliana plants identified 33 novel mutations in the APS1 gene, including 21 missense mutations in the protein coding region. High throughput measurements using a robotised cycling assay showed that maximal AGPase activity in the aps1 mutants varied from <15 to 117% of wild type (WT), and that the kinetic properties of the enzyme were altered in several lines, indicating a role for the substituted amino acid residues in catalysis or substrate binding. These results validate the concept of using such a platform for efficient high-throughput screening of very large populations of mutants, natural accessions or introgression lines. AGPase was estimated to have a flux control coefficient of 0.20, indicating that the enzyme exerted only modest control over the rate of starch synthesis in plants grown under short day conditions (8 h light/16 h dark) with an irradiance of 150 μmol quanta m(-2)s(-1). Redox activation of the enzyme, via reduction of the intermolecular disulphide bridge between the two small subunits, was increased in several lines. This was sometimes, but not always, associated with a decrease in the abundance of the APS1 protein. In conclusion, the TILLING technique was used to generate an allelic series of aps1 mutants in A. thaliana that revealed new insights into the multi-layered regulation of AGPase. These mutants offer some advantages over the available loss-of-function mutants, e.g. adg1, for investigating the effects of subtle changes in the enzyme's activity on the rate of starch synthesis.
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Affiliation(s)
- Nadja Hädrich
- Max Planck Institute of Molecular Plant Physiology, Wissenschaftspark Golm, Am Mühlenberg 1, Potsdam-Golm, Germany
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16
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Tungtur S, Parente DJ, Swint-Kruse L. Functionally important positions can comprise the majority of a protein's architecture. Proteins 2011; 79:1589-608. [PMID: 21374721 DOI: 10.1002/prot.22985] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2010] [Revised: 12/08/2010] [Accepted: 12/15/2010] [Indexed: 01/13/2023]
Abstract
Concomitant with the genomic era, many bioinformatics programs have been developed to identify functionally important positions from sequence alignments of protein families. To evaluate these analyses, many have used the LacI/GalR family and determined whether positions predicted to be "important" are validated by published experiments. However, we previously noted that predictions do not identify all of the experimentally important positions present in the linker regions of these homologs. In an attempt to reconcile these differences, we corrected and expanded the LacI/GalR sequence set commonly used in sequence/function analyses. Next, a variety of analyses were carried out (1) for the entire LacI/GalR sequence set and (2) for a subset of homologs with functionally-important "YxPxxxAxxL" motifs in their linkers. This strategy was devised to determine whether predictions could be improved by knowledge-based sequence sorting and-for some analyses-did increase the number of linker positions identified. However, two functionally important linker positions were not reliably identified by any analysis. Finally, we compared the new predictions to all known experimental data for E. coli LacI and three homologous linkers. From these, we estimate that >50% of positions are important to the functions of the LacI/GalR homologs. In corollary, neutral positions might occur less frequently and might be easier to detect in sequence analyses. Although analyses have successfully guided mutations that partially exchange protein functions, a better experimental understanding of the sequence/function relationships in protein families would be helpful for uncovering the remaining rules used by nature to evolve new protein functions.
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Affiliation(s)
- Sudheer Tungtur
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, MSN 3030, Kansas City, Kansas 66160, USA
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17
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Kemper S, Patel MK, Errey JC, Davis BG, Jones JA, Claridge TDW. Group epitope mapping considering relaxation of the ligand (GEM-CRL): including longitudinal relaxation rates in the analysis of saturation transfer difference (STD) experiments. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2010; 203:1-10. [PMID: 20022272 DOI: 10.1016/j.jmr.2009.11.015] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2009] [Revised: 11/20/2009] [Accepted: 11/23/2009] [Indexed: 05/28/2023]
Abstract
In the application of saturation transfer difference (STD) experiments to the study of protein-ligand interactions, the relaxation of the ligand is one of the major influences on the experimentally observed STD factors, making interpretation of these difficult when attempting to define a group epitope map (GEM). In this paper, we describe a simplification of the relaxation matrix that may be applied under specified experimental conditions, which results in a simplified equation reflecting the directly transferred magnetisation rate from the protein onto the ligand, defined as the summation over the whole protein of the protein-ligand cross-relaxation multiplied by with the fractional saturation of the protein protons. In this, the relaxation of the ligand is accounted for implicitly by inclusion of the experimentally determined longitudinal relaxation rates. The conditions under which this "group epitope mapping considering relaxation of the ligand" (GEM-CRL) can be applied were tested on a theoretical model system, which demonstrated only minor deviations from that predicted by the full relaxation matrix calculations (CORCEMA-ST) [7]. Furthermore, CORCEMA-ST calculations of two protein-saccharide complexes (Jacalin and TreR) with known crystal structures were performed and compared with experimental GEM-CRL data. It could be shown that the GEM-CRL methodology is superior to the classical group epitope mapping approach currently used for defining ligand-protein proximities. GEM-CRL is also useful for the interpretation of CORCEMA-ST results, because the transferred magnetisation rate provides an additional parameter for the comparison between measured and calculated values. The independence of this parameter from the above mentioned factors can thereby enhance the value of CORCEMA-ST calculations.
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Affiliation(s)
- Sebastian Kemper
- Chemistry Research Laboratory, Department of Chemistry, University of Oxford, Mansfield Road, Oxford OX1 3TA, UK
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18
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Xu QS, Ankoudinova I, Lou Y, Yokota H, Kim R, Kim SH. Crystal structure of a transcriptional activator of comK gene from Bacillus halodurans. Proteins 2009; 69:409-14. [PMID: 17636568 DOI: 10.1002/prot.21292] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Qian Steven Xu
- Division of Physical Biosciences, Lawrence Berkeley National Laboratory, Berkeley Structural Genomics Center, Berkeley, California 94720, USA
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19
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Pérez-Victoria I, Kemper S, Patel MK, Edwards JM, Errey JC, Primavesi LF, Paul MJ, Claridge TDW, Davis BG. Saturation transfer difference NMR reveals functionally essential kinetic differences for a sugar-binding repressor protein. Chem Commun (Camb) 2009:5862-4. [DOI: 10.1039/b913489a] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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20
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Lee SJ, Surma M, Hausner W, Thomm M, Boos W. The role of TrmB and TrmB-like transcriptional regulators for sugar transport and metabolism in the hyperthermophilic archaeon Pyrococcus furiosus. Arch Microbiol 2008; 190:247-56. [DOI: 10.1007/s00203-008-0378-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2008] [Revised: 03/17/2008] [Accepted: 04/25/2008] [Indexed: 11/29/2022]
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21
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Pennetier C, Domínguez-Ramírez L, Plumbridge J. Different regions of Mlc and NagC, homologous transcriptional repressors controlling expression of the glucose and N-acetylglucosamine phosphotransferase systems in Escherichia coli, are required for inducer signal recognition. Mol Microbiol 2007; 67:364-77. [PMID: 18067539 DOI: 10.1111/j.1365-2958.2007.06041.x] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Mlc and NagC are two homologous transcription factors which bind to similar DNA targets but for which the inducing signals and mechanisms of activation are very different. Displacing Mlc from its DNA binding sites necessitates its sequestration to the inner membrane via an interaction with PtsG (EIICB(Glc)), while NagC is displaced from its DNA targets by interacting with GlcNAc6P. We have isolated mutations in both proteins which prevent the inactivation of the repressors by growth on glucose or GlcNAc. These mutations are located in different and specific regions of each protein. For Mlc changes at the C-terminal make it a constitutive repressor and also prevent it from binding to EIIB(Glc). Mutations in NagC, at positions which form a structural motif resembling a glucose binding site in Mlc, produce permanently repressing forms of NagC, suggesting that this motif forms a GlcNAc6P binding site in NagC. The pattern of repression by chimeric proteins of NagC and Mlc confirms the importance of the C-terminal region of Mlc for both repression and inducer binding and demonstrate that the helix-turn-helix DNA-binding motif is not sufficient to determine the specificity of interaction of the repressor with DNA.
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Affiliation(s)
- Carole Pennetier
- Institut de Biologie Physico-Chimique (UPR9073-CNRS), 13 rue Pierre et Marie Curie, 75005 Paris, France
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22
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Rao KN, Kumaran D, Seetharaman J, Bonanno JB, Burley SK, Swaminathan S. Crystal structure of trehalose-6-phosphate phosphatase-related protein: biochemical and biological implications. Protein Sci 2006; 15:1735-44. [PMID: 16815921 PMCID: PMC2242562 DOI: 10.1110/ps.062096606] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2006] [Revised: 03/30/2006] [Accepted: 04/04/2006] [Indexed: 10/24/2022]
Abstract
We report here the crystal structure of a trehalose-6-phosphate phosphatase-related protein (T6PP) from Thermoplasma acidophilum, TA1209, determined by the dual-wavelength anomalous diffraction (DAD) method. T6PP is a member of the haloacid dehalogenase (HAD) superfamily with significant sequence homology with trehalose-6-phosphate phosphatase, phosphoserine phosphatase, P-type ATPases and other members of the family. T6PP possesses a core domain of known alpha/beta-hydrolase fold, characteristic of the HAD family, and a cap domain, with a tertiary fold consisting of a four-stranded beta-sheet with two alpha-helices on one side of the sheet. An active-site magnesium ion and a glycerol molecule bound at the interface between the two domains provide insight into the mode of substrate binding by T6PP. A trehalose-6-phosphate molecule modeled into a cage formed by the two domains makes favorable interactions with the protein molecule. We have confirmed that T6PP is a trehalose phosphatase from amino acid sequence, three-dimensional structure, and biochemical assays.
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23
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Franco IS, Mota LJ, Soares CM, de Sá-Nogueira I. Functional domains of the Bacillus subtilis transcription factor AraR and identification of amino acids important for nucleoprotein complex assembly and effector binding. J Bacteriol 2006; 188:3024-36. [PMID: 16585763 PMCID: PMC1446991 DOI: 10.1128/jb.188.8.3024-3036.2006] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The Bacillus subtilis AraR transcription factor represses at least 13 genes required for the extracellular degradation of arabinose-containing polysaccharides, transport of arabinose, arabinose oligomers, xylose, and galactose, intracellular degradation of arabinose oligomers, and further catabolism of this sugar. AraR exhibits a chimeric organization comprising a small N-terminal DNA-binding domain that contains a winged helix-turn-helix motif similar to that seen with the GntR family and a larger C-terminal domain homologous to that of the LacI/GalR family. Here, a model for AraR was derived based on the known crystal structures of the FadR and PurR regulators from Escherichia coli. We have used random mutagenesis, deletion, and construction of chimeric LexA-AraR fusion proteins to map the functional domains of AraR required for DNA binding, dimerization, and effector binding. Moreover, predictions for the functional role of specific residues were tested by site-directed mutagenesis. In vivo analysis identified particular amino acids required for dimer assembly, formation of the nucleoprotein complex, and composition of the sugar-binding cleft. This work presents a structural framework for the function of AraR and provides insight into the mechanistic mode of action of this modular repressor.
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Affiliation(s)
- Irina Saraiva Franco
- Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da República, Apt. 127, 2781-901 Oeiras, Portugal
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Krug M, Lee SJ, Diederichs K, Boos W, Welte W. Crystal Structure of the Sugar Binding Domain of the Archaeal Transcriptional Regulator TrmB. J Biol Chem 2006; 281:10976-82. [PMID: 16473881 DOI: 10.1074/jbc.m512809200] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
TrmB is an alpha-glucoside-sensing transcriptional regulator controlling two operons encoding maltose/trehalose and maltodextrin ABC transporters of Pyrococcus furiosus. The crystal structure of an N-terminal truncated derivative of TrmB (amino acids 2-109 deleted; TrmB(delta2-109)) was solved at 1.5 A resolution. This protein has lost its DNA binding domain but has retained its sugar recognition site. The structure represents a novel sugar-binding fold. TrmB(delta2-109) bound maltose, glucose, sucrose, and maltotriose, exhibiting Kd values of 6.8, 25, 34, and 160 microM, respectively. TrmB(delta2-109) behaved as a monomer in dilute buffer solution in contrast to the full-length protein, which is a dimer. Co-crystallization with bound maltose identified a binding site involving seven amino acid residues: Ser229, Asn305, Gly320, Met321, Val324, Ile325, and Glu326. Six of these residues interact with the nonreducing glucosyl residue of maltose. The nonreducing glucosyl residue is shared by all substrates bound to TrmB, suggesting it as a common recognition motif.
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Affiliation(s)
- Michael Krug
- Department of Biology, University of Konstanz, 78457 Konstanz, Germany
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25
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Abstract
Escherichia coli and Salmonella enterica serovar Typhimurium exhibit a remarkable versatility in the usage of different sugars as the sole source of carbon and energy, reflecting their ability to make use of the digested meals of mammalia and of the ample offerings in the wild. Degradation of sugars starts with their energy-dependent uptake through the cytoplasmic membrane and is carried on further by specific enzymes in the cytoplasm, destined finally for degradation in central metabolic pathways. As variant as the different sugars are, the biochemical strategies to act on them are few. They include phosphorylation, keto-enol isomerization, oxido/reductions, and aldol cleavage. The catabolic repertoire for using carbohydrate sources is largely the same in E. coli and in serovar Typhimurium. Nonetheless, significant differences are found, even among the strains and substrains of each species. We have grouped the sugars to be discussed according to their first step in metabolism, which is their active transport, and follow their path to glycolysis, catalyzed by the sugar-specific enzymes. We will first discuss the phosphotransferase system (PTS) sugars, then the sugars transported by ATP-binding cassette (ABC) transporters, followed by those that are taken up via proton motive force (PMF)-dependent transporters. We have focused on the catabolism and pathway regulation of hexose and pentose monosaccharides as well as the corresponding sugar alcohols but have also included disaccharides and simple glycosides while excluding polysaccharide catabolism, except for maltodextrins.
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Affiliation(s)
- Christoph Mayer
- Fachbereich Biologie, Universität Konstanz, 78457 Konstanz, Germany
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Miller ST, Xavier KB, Campagna SR, Taga ME, Semmelhack MF, Bassler BL, Hughson FM. Salmonella typhimurium recognizes a chemically distinct form of the bacterial quorum-sensing signal AI-2. Mol Cell 2004; 15:677-87. [PMID: 15350213 DOI: 10.1016/j.molcel.2004.07.020] [Citation(s) in RCA: 383] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2004] [Revised: 06/11/2004] [Accepted: 06/17/2004] [Indexed: 10/26/2022]
Abstract
Bacterial populations use cell-cell communication to coordinate community-wide regulation of processes such as biofilm formation, virulence, and bioluminescence. This phenomenon, termed quorum sensing, is mediated by small molecule signals known as autoinducers. While most autoinducers are species specific, autoinducer-2 (AI-2), first identified in the marine bacterium Vibrio harveyi, is produced and detected by many Gram-negative and Gram-positive bacteria. The crystal structure of the V. harveyi AI-2 signaling molecule bound to its receptor protein revealed an unusual furanosyl borate diester. Here, we present the crystal structure of a second AI-2 signal binding protein, LsrB from Salmonella typhimurium. We find that LsrB binds a chemically distinct form of the AI-2 signal, (2R,4S)-2-methyl-2,3,3,4-tetrahydroxytetrahydrofuran (R-THMF), that lacks boron. Our results demonstrate that two different species of bacteria recognize two different forms of the autoinducer signal, both derived from 4,5-dihydroxy-2,3-pentanedione (DPD), and reveal new sophistication in the chemical lexicon used by bacteria in interspecies signaling.
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Affiliation(s)
- Stephen T Miller
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
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27
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Wilson RA, Maughan WN, Kremer L, Besra GS, Fütterer K. The structure of Mycobacterium tuberculosis MPT51 (FbpC1) defines a new family of non-catalytic alpha/beta hydrolases. J Mol Biol 2004; 335:519-30. [PMID: 14672660 DOI: 10.1016/j.jmb.2003.11.001] [Citation(s) in RCA: 37] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Mycobacterium tuberculosis, the causative agent of tuberculosis, is known to secrete a number of highly immunogenic proteins that are thought to confer pathogenicity, in part, by mediating binding to host tissues. Among these secreted proteins are the trimeric antigen 85 (Ag85) complex and the related MPT51 protein, also known as FbpC1. While the physiological function of Ag85, a mycolyltransferase required for the biosynthesis of the cell wall component alpha,alpha'-trehalose dimycolate (or cord factor), has been identified recently, the function of the closely related MPT51 (approximately 40% identity with the Ag85 components) remains to be established. The crystal structure of M.tuberculosis MPT51, determined to 1.7 A resolution, shows that MPT51, like the Ag85 components Ag85B and Ag85C2, folds as an alpha/beta hydrolase, but it does not contain any of the catalytic elements required for mycolyltransferase activity. Moreover, the absence of a recognizable alpha,alpha'-trehalose monomycolate-binding site and the failure to detect an active site suggest that the function of MPT51 is of a non-enzymatic nature and that MPT51 may in fact represent a new family of non-catalytic alpha/beta hydrolases. Previous experimental evidence and the structural similarity to some integrins and carbohydrate-binding proteins led to the hypothesis that MPT51 might have a role in host tissue attachment, whereby ligands may include the serum protein fibronectin and small sugars.
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Affiliation(s)
- Rosalind A Wilson
- School of Biosciences, The University of Birmingham, Edgabston, Birmingham B15 2TT, UK
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28
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Swint-Kruse L, Elam CR, Lin JW, Wycuff DR, Shive Matthews K. Plasticity of quaternary structure: twenty-two ways to form a LacI dimer. Protein Sci 2001; 10:262-76. [PMID: 11266612 PMCID: PMC2373939 DOI: 10.1110/ps.35801] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The repressor proteins of the LacI/GalR family exhibit significant similarity in their secondary and tertiary structures despite less than 35% identity in their primary sequences. Furthermore, the core domains of these oligomeric repressors, which mediate dimerization, are homologous with the monomeric periplasmic binding proteins, extending the issue of plasticity to quaternary structure. To elucidate the determinants of assembly, a structure-based alignment has been created for three repressors and four periplasmic binding proteins. Contact maps have also been constructed for the three repressor interfaces to distinguish any conserved interactions. These analyses show few strict requirements for assembly of the core N-subdomain interface. The interfaces of repressor core C-subdomains are well conserved at the structural level, and their primary sequences differ significantly from the monomeric periplasmic binding proteins at positions equivalent to LacI 281 and 282. However, previous biochemical and phenotypic analyses indicate that LacI tolerates many mutations at 281. Mutations at LacI 282 were shown to abrogate assembly, but for Y282D this could be compensated by a second-site mutation in the core N-subdomain at K84 to L or A. Using the link between LacI assembly and function, we have further identified 22 second-site mutations that compensate the Y282D dimerization defect in vivo. The sites of these mutations fall into several structural regions, each of which may influence assembly by a different mechanism. Thus, the 360-amino acid scaffold of LacI allows plasticity of its quaternary structure. The periplasmic binding proteins may require only minimal changes to facilitate oligomerization similar to the repressor proteins.
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Affiliation(s)
- L Swint-Kruse
- The W. M. Keck Center for Computational Biology, Rice University, Houston, Texas 77005, USA.
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29
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Metzler DE, Metzler CM, Sauke DJ. Some Pathways of Carbohydrate Metabolism. Biochemistry 2001. [DOI: 10.1016/b978-012492543-4/50023-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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30
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Johnson JM, Church GM. Predicting ligand-binding function in families of bacterial receptors. Proc Natl Acad Sci U S A 2000; 97:3965-70. [PMID: 10737762 PMCID: PMC18125 DOI: 10.1073/pnas.050580897] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The three-dimensional fold of a new protein sequence can often be inferred directly from sequence homology to a protein of known structure. The function of a new protein sequence is more difficult to predict, however, since homologues can have different molecular and cellular functions. To develop and automate computational methods for determining molecular function, we have analyzed ligand-binding specificity in two related families of binding proteins. One of these families includes Escherichia coli lactose repressor and ribose-binding protein, and the other includes E. coli sulfate- and phosphate-binding proteins. These proteins have similar folds but varying specificity, binding many different small molecules, including mono- and disaccharides, purines, oxyanions, ferric iron, and polyamines. Starting from template structural alignments, alignments of over 90 sequences per family were generated by iterative database searches with hidden Markov models. Phylogenetic trees were made of full-length sequences and of subsets of residues lining the binding cleft, to determine whether subbranches of the trees correlate with ligand-binding preference. Automated analyses of residues in the binding pocket were also used to predict ligand-binding function for many uncharacterized database sequences and to identify specific side chain-ligand contacts in proteins without solved structures. Our results demonstrate the utility of anchoring functional annotation within a protein family context.
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Affiliation(s)
- J M Johnson
- Graduate Program in Biophysics and Department of Genetics, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA
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