Literature DB >> 19161840

A proteomic approach to the analysis of RNA degradosome composition in Escherichia coli.

Pierluigi Mauri1, Gianni Dehò.   

Abstract

The RNA degradosome is a bacterial protein machine devoted to RNA degradation and processing. In Escherichia coli, it is typically composed of the endoribonuclease RNase E, which also serves as a scaffold for the other components: the exoribonuclease PNPase, the RNA helicase RhlB, and enolase. The variable presence of additional proteins, however, suggests that the degradosome is a flexible machine that may vary its composition in response to different conditions. Direct analysis of large protein complexes, together with simplified purification procedures, can facilitate qualitative and quantitative identification of RNA degradosome components under different physiologic and genetic conditions and can help to explain their role in the bacterial cell (see also Chapters 4, 11, 19, 20 and 22 regarding methods for the studying the degradosome and other multiprotein complexes in this volume. Herewith we describe the application of multidimensional protein identification technology (MudPIT) in the rapid and quantitative identification of RNA degradosome components. RNA degradosome preparations obtained from specific conditions are enzymatically digested. The resulting peptides are fractionated using two-dimensional (ion-exchange and reversed-phase) chromatography and analyzed by tandem mass spectrometry. Bioinformatic analysis with the SEQUEST algorithm, which correlates experimentally obtained mass spectra with those predicted from peptide sequences in proteomic and translated genomic databases, allows identification of the corresponding proteins that compose the complex. The protein constituents of two or more degradosome samples are then compared to obtain a rapid evaluation of qualitative and quantitative differences in protein composition. Quantitative analysis is based on the observation that changes in relative protein abundance among different samples are reflected by statistical parameters (score values) assigned to each protein component of the RNA degradosome identified by the MudPIT approach. This correlation can be validated by independent methods such as Western blotting and determination of enzymatic activities. This fully automated procedure may be applied to the characterization of any complex protein mixture.

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Year:  2008        PMID: 19161840     DOI: 10.1016/S0076-6879(08)02206-4

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  16 in total

1.  The response regulator SprE (RssB) is required for maintaining poly(A) polymerase I-degradosome association during stationary phase.

Authors:  Valerie J Carabetta; Thomas J Silhavy; Ileana M Cristea
Journal:  J Bacteriol       Date:  2010-05-14       Impact factor: 3.490

2.  S1 ribosomal protein and the interplay between translation and mRNA decay.

Authors:  Francesco Delvillani; Giulia Papiani; Gianni Dehò; Federica Briani
Journal:  Nucleic Acids Res       Date:  2011-06-17       Impact factor: 16.971

3.  Gene and protein expression in response to different growth temperatures and oxygen availability in Burkholderia thailandensis.

Authors:  Clelia Peano; Fabrizio Chiaramonte; Sara Motta; Alessandro Pietrelli; Sebastien Jaillon; Elio Rossi; Clarissa Consolandi; Olivia L Champion; Stephen L Michell; Luca Freddi; Luigi Falciola; Fabrizio Basilico; Cecilia Garlanda; Pierluigi Mauri; Gianluca De Bellis; Paolo Landini
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

4.  Proteomic analysis of urine exosomes reveals renal tubule response to leptospiral colonization in experimentally infected rats.

Authors:  Satish P RamachandraRao; Michael A Matthias; Chanthel Kokoy-Mondragon; Chanthel-Kokoy Mondrogon; Eamon Aghania; Cathleen Park; Casey Kong; Michelle Ishaya; Assael Madrigal; Jennifer Horng; Roni Khoshaba; Anousone Bounkhoun; Fabrizio Basilico; Antonella De Palma; Anna Maria Agresta; Linda Awdishu; Robert K Naviaux; Joseph M Vinetz; Pierluigi Mauri
Journal:  PLoS Negl Trop Dis       Date:  2015-03-20

5.  The polyglutamine protein ataxin-3 enables normal growth under heat shock conditions in the methylotrophic yeast Pichia pastoris.

Authors:  Marcella Bonanomi; Valentina Roffia; Antonella De Palma; Alessio Lombardi; Francesco Antonio Aprile; Cristina Visentin; Paolo Tortora; Pierluigi Mauri; Maria Elena Regonesi
Journal:  Sci Rep       Date:  2017-10-17       Impact factor: 4.379

6.  Combination of Metabolomic and Proteomic Analysis Revealed Different Features among Lactobacillus delbrueckii Subspecies bulgaricus and lactis Strains While In Vivo Testing in the Model Organism Caenorhabditis elegans Highlighted Probiotic Properties.

Authors:  Elena Zanni; Emily Schifano; Sara Motta; Fabio Sciubba; Claudio Palleschi; Pierluigi Mauri; Giuditta Perozzi; Daniela Uccelletti; Chiara Devirgiliis; Alfredo Miccheli
Journal:  Front Microbiol       Date:  2017-06-28       Impact factor: 5.640

7.  Galectin-3: an early predictive biomarker of modulation of airway remodeling in patients with severe asthma treated with omalizumab for 36 months.

Authors:  Anna Maria Riccio; Pierluigi Mauri; Laura De Ferrari; Rossana Rossi; Dario Di Silvestre; Louise Benazzi; Alessandra Chiappori; Roberto Walter Dal Negro; Claudio Micheletto; Giorgio Walter Canonica
Journal:  Clin Transl Allergy       Date:  2017-03-09       Impact factor: 5.871

8.  Availability of MudPIT data for classification of biological samples.

Authors:  Dario Di Silvestre; Italo Zoppis; Francesca Brambilla; Valeria Bellettato; Giancarlo Mauri; Pierluigi Mauri
Journal:  J Clin Bioinforma       Date:  2013-01-14

9.  Analysis of Pseudomonas aeruginosa cell envelope proteome by capture of surface-exposed proteins on activated magnetic nanoparticles.

Authors:  Davide Vecchietti; Dario Di Silvestre; Matteo Miriani; Francesco Bonomi; Mauro Marengo; Alessandra Bragonzi; Lara Cova; Eleonora Franceschi; Pierluigi Mauri; Giovanni Bertoni
Journal:  PLoS One       Date:  2012-11-30       Impact factor: 3.240

10.  Dissecting Escherichia coli outer membrane biogenesis using differential proteomics.

Authors:  Alessandra M Martorana; Sara Motta; Dario Di Silvestre; Federica Falchi; Gianni Dehò; Pierluigi Mauri; Paola Sperandeo; Alessandra Polissi
Journal:  PLoS One       Date:  2014-06-26       Impact factor: 3.240

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