Literature DB >> 12867470

Initial proteome analysis of model microorganism Haemophilus influenzae strain Rd KW20.

Eugene Kolker1, Samuel Purvine, Michael Y Galperin, Serg Stolyar, David R Goodlett, Alexey I Nesvizhskii, Andrew Keller, Tao Xie, Jimmy K Eng, Eugene Yi, Leroy Hood, Alex F Picone, Tim Cherny, Brian C Tjaden, Andrew F Siegel, Thomas J Reilly, Kira S Makarova, Bernhard O Palsson, Arnold L Smith.   

Abstract

The proteome of Haemophilus influenzae strain Rd KW20 was analyzed by liquid chromatography (LC) coupled with ion trap tandem mass spectrometry (MS/MS). This approach does not require a gel electrophoresis step and provides a rapidly developed snapshot of the proteome. In order to gain insight into the central metabolism of H. influenzae, cells were grown microaerobically and anaerobically in a rich medium and soluble and membrane proteins of strain Rd KW20 were proteolyzed with trypsin and directly examined by LC-MS/MS. Several different experimental and computational approaches were utilized to optimize the proteome coverage and to ensure statistically valid protein identification. Approximately 25% of all predicted proteins (open reading frames) of H. influenzae strain Rd KW20 were identified with high confidence, as their component peptides were unambiguously assigned to tandem mass spectra. Approximately 80% of the predicted ribosomal proteins were identified with high confidence, compared to the 33% of the predicted ribosomal proteins detected by previous two-dimensional gel electrophoresis studies. The results obtained in this study are generally consistent with those obtained from computational genome analysis, two-dimensional gel electrophoresis, and whole-genome transposon mutagenesis studies. At least 15 genes originally annotated as conserved hypothetical were found to encode expressed proteins. Two more proteins, previously annotated as predicted coding regions, were detected with high confidence; these proteins also have close homologs in related bacteria. The direct proteomics approach to studying protein expression in vivo reported here is a powerful method that is applicable to proteome analysis of any (micro)organism.

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Year:  2003        PMID: 12867470      PMCID: PMC165749          DOI: 10.1128/JB.185.15.4593-4602.2003

Source DB:  PubMed          Journal:  J Bacteriol        ISSN: 0021-9193            Impact factor:   3.490


  62 in total

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Authors:  C S Spahr; M T Davis; M D McGinley; J H Robinson; E J Bures; J Beierle; J Mort; P L Courchesne; K Chen; R C Wahl; W Yu; R Luethy; S D Patterson
Journal:  Proteomics       Date:  2001-01       Impact factor: 3.984

2.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

Authors:  Andrew Keller; Alexey I Nesvizhskii; Eugene Kolker; Ruedi Aebersold
Journal:  Anal Chem       Date:  2002-10-15       Impact factor: 6.986

3.  The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.

Authors:  Jason A Papin; Nathan D Price; Jeremy S Edwards; Bernhard Ø Palsson B
Journal:  J Theor Biol       Date:  2002-03-07       Impact factor: 2.691

4.  Functional organization of the yeast proteome by systematic analysis of protein complexes.

Authors:  Anne-Claude Gavin; Markus Bösche; Roland Krause; Paola Grandi; Martina Marzioch; Andreas Bauer; Jörg Schultz; Jens M Rick; Anne-Marie Michon; Cristina-Maria Cruciat; Marita Remor; Christian Höfert; Malgorzata Schelder; Miro Brajenovic; Heinz Ruffner; Alejandro Merino; Karin Klein; Manuela Hudak; David Dickson; Tatjana Rudi; Volker Gnau; Angela Bauch; Sonja Bastuck; Bettina Huhse; Christina Leutwein; Marie-Anne Heurtier; Richard R Copley; Angela Edelmann; Erich Querfurth; Vladimir Rybin; Gerard Drewes; Manfred Raida; Tewis Bouwmeester; Peer Bork; Bertrand Seraphin; Bernhard Kuster; Gitte Neubauer; Giulio Superti-Furga
Journal:  Nature       Date:  2002-01-10       Impact factor: 49.962

5.  From proteins to proteomes: large scale protein identification by two-dimensional electrophoresis and amino acid analysis.

Authors:  M R Wilkins; C Pasquali; R D Appel; K Ou; O Golaz; J C Sanchez; J X Yan; A A Gooley; G Hughes; I Humphery-Smith; K L Williams; D F Hochstrasser
Journal:  Biotechnology (N Y)       Date:  1996-01

6.  Gene expression changes triggered by exposure of Haemophilus influenzae to novobiocin or ciprofloxacin: combined transcription and translation analysis.

Authors:  H Gmuender; K Kuratli; C P Gray; W Keck; S Evers
Journal:  Genome Res       Date:  2001-01       Impact factor: 9.043

7.  Relationship between bacterial flora in sputum and functional impairment in patients with acute exacerbations of COPD. Study Group of Bacterial Infection in COPD.

Authors:  M Miravitlles; C Espinosa; E Fernández-Laso; J A Martos; J A Maldonado; M Gallego
Journal:  Chest       Date:  1999-07       Impact factor: 9.410

8.  Analysis of quantitative proteomic data generated via multidimensional protein identification technology.

Authors:  Michael P Washburn; Ryan Ulaszek; Cosmin Deciu; David M Schieltz; John R Yates
Journal:  Anal Chem       Date:  2002-04-01       Impact factor: 6.986

9.  Strategies towards a better understanding of antibiotic action: folate pathway inhibition in Haemophilus influenzae as an example.

Authors:  S Evers; K Di Padova; M Meyer; M Fountoulakis; W Keck; C P Gray
Journal:  Electrophoresis       Date:  1998-08       Impact factor: 3.535

10.  Conserved 'hypothetical' proteins: new hints and new puzzles.

Authors:  M Y Galperin
Journal:  Comp Funct Genomics       Date:  2001
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  16 in total

1.  Computational analysis of unassigned high-quality MS/MS spectra in proteomic data sets.

Authors:  Kang Ning; Damian Fermin; Alexey I Nesvizhskii
Journal:  Proteomics       Date:  2010-07       Impact factor: 3.984

Review 2.  'Conserved hypothetical' proteins: prioritization of targets for experimental study.

Authors:  Michael Y Galperin; Eugene V Koonin
Journal:  Nucleic Acids Res       Date:  2004-10-12       Impact factor: 16.971

3.  Crystal structure of the bacterial YhcH protein indicates a role in sialic acid catabolism.

Authors:  Alexey Teplyakov; Galina Obmolova; John Toedt; Michael Y Galperin; Gary L Gilliland
Journal:  J Bacteriol       Date:  2005-08       Impact factor: 3.490

4.  Proteomic analysis of Psychrobacter cryohalolentis K5 during growth at subzero temperatures.

Authors:  Corien Bakermans; Sandra L Tollaksen; Carol S Giometti; Curtis Wilkerson; James M Tiedje; Michael F Thomashow
Journal:  Extremophiles       Date:  2006-11-23       Impact factor: 2.395

5.  Modeling sequence and function similarity between proteins for protein functional annotation.

Authors:  Roger Higdon; Brenton Louie; Eugene Kolker
Journal:  Proc Int Symp High Perform Distrib Comput       Date:  2010

6.  DNA-binding by Haemophilus influenzae and Escherichia coli YbaB, members of a widely-distributed bacterial protein family.

Authors:  Anne E Cooley; Sean P Riley; Keith Kral; M Clarke Miller; Edward DeMoll; Michael G Fried; Brian Stevenson
Journal:  BMC Microbiol       Date:  2009-07-13       Impact factor: 3.605

7.  Proteomic expression profiling of Haemophilus influenzae grown in pooled human sputum from adults with chronic obstructive pulmonary disease reveal antioxidant and stress responses.

Authors:  Jun Qu; Alan J Lesse; Aimee L Brauer; Jin Cao; Steven R Gill; Timothy F Murphy
Journal:  BMC Microbiol       Date:  2010-06-01       Impact factor: 3.605

8.  VapC-1 of nontypeable Haemophilus influenzae is a ribonuclease.

Authors:  Dayle A Daines; Mack H Wu; Sarah Y Yuan
Journal:  J Bacteriol       Date:  2007-05-11       Impact factor: 3.490

9.  2-DE analysis indicates that Acinetobacter baumannii displays a robust and versatile metabolism.

Authors:  Nelson C Soares; Maria P Cabral; José R Parreira; Carmen Gayoso; Maria J Barba; Germán Bou
Journal:  Proteome Sci       Date:  2009-09-28       Impact factor: 2.480

10.  A statistical model of protein sequence similarity and function similarity reveals overly-specific function predictions.

Authors:  Brenton Louie; Roger Higdon; Eugene Kolker
Journal:  PLoS One       Date:  2009-10-21       Impact factor: 3.240

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