Skip to main content
SpringerLink
Log in

Utility of gel-free, label-free shotgun proteomics approaches to investigate microorganisms

  • Mini-Review
  • Published:
Applied Microbiology and Biotechnology Aims and scope Submit manuscript

Abstract

This review will examine the current situation with label-free, quantitative, shotgun-oriented proteomics technology and discuss the advantages and limitations associated with its capability in capturing and quantifying large portions of proteomes of microorganisms. Such an approach allows (1) comparisons between physiological or genetic states of organisms at the protein level, (2) ‘painting’ of proteomic data onto genome data-based metabolic maps, (3) enhancement of the utility of genomic data and finally (4) surveying of non-genome sequenced microorganisms by taking advantage of available inferred protein data in order to gain new insights into strain-dependent metabolic or physiological capacities. The technology essentially is a powerful addition to systems biology with a capacity to be used to ask hypothesis-driven ‘top-down’ questions or for more empirical ‘bottom-up’ exploration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Al-Shahrour F, Carbonell J, Minguez P, Goetz S, Conesa A, Tárraga J, Medina I, Alloza E, Montaner D, Dopazo J (2010) Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments. Nucleic Acids Res 36:W341–W346

    Article  Google Scholar 

  • Andrew SM, Titus JA, Zumstein L (2001) Dialysis and concentration of protein solutions. Curr Prot Immun. doi:10.1002/0471142735.ima03hs21, Appendix 3H

    Google Scholar 

  • Ansong C, Purvibe SO, Adkins JN, Lipton MS, Smith RD (2010) Proteogenomics: needs and roles to be filled by proteomics in genome annotation. Brief Funct Genom 7:50–62

    Article  Google Scholar 

  • Becher D, Hempel K, Sievers S, Zühlke D, Pané-Farré J, Otto A, Fuchs S, Albrecht D, Bernhardt J, Engelmann S, Völker U, van Dijl JM, Hecker M (2009) A proteomic view of an important human pathogen—towards the quantification of the entire Staphylococcus aureus proteome. PLoS ONE 4:e8176

    Article  Google Scholar 

  • Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc B 57:289–300

    Google Scholar 

  • Boorsma A, Foat BC, Vis D, Klis F, Bussemaker HJ (2005) T-profiler: scoring the activity of predefined groups of genes using gene expression data. Nucleic Acids Res 33:W592–W595

    Article  CAS  Google Scholar 

  • Broberg CA, Clark DD (2010) Shotgun proteomics of Xanthobacter autotrophicus Py2 reveals proteins specific to growth on propylene. Arch Microbiol 192:945–957

    Article  CAS  Google Scholar 

  • Cerqueira FR, Graber A, Schwikowski B, Baumgartner C (2010) MUDE: a new approach for optimizing sensitivity in the target-decoy search strategy for large-scale peptide/protein identification. J Proteome Res 9:2265–2277

    Article  CAS  Google Scholar 

  • Choi H, Fermin D, Nesvizhskii AI (2008) Significance analysis of spectral count data in label-free shotgun proteomics. Mol Cell Prot 7:2373–2385

    Article  CAS  Google Scholar 

  • Christie-Oleza JA, Armengaud J (2010) In-depth analysis of exoproteomes from marine bacteria by shotgun liquid chromatography–tandem mass spectrometry: the Ruegeria pomeroyi DSS-3 case-study. Mar Drugs 8:2223–2239

    Article  CAS  Google Scholar 

  • Conrads TP, Alving K, Veenstra TD, Belov ME, Anderson GA, Anderson DJ, Lipton MS, Pasa-Tolic L, Udseth HR, Chrisler WB, Thrall BD, Smith RD (2001) Quantitative analysis of bacterial and mammalian proteomes using a combination of cysteine affinity tags and 15N-metabolic labeling. Anal Chem 73:2132–2139

    Article  CAS  Google Scholar 

  • Cooper B, Feng JA, Garrett WM (2010) Relative, label-free protein quantitation: spectral counting error statistics from nine replicate MudPIT samples. J Am Soc Mass Spectrom 21:1534–1546

    Article  CAS  Google Scholar 

  • de Hoog CL, Mann M (2004) Proteomics. Annu Rev Genomics Hum Genet 5:267–293

    Article  Google Scholar 

  • Dowell JA, Frost DC, Zhang J, Li L (2008) Comparison of two-dimensional fractionation techniques for shotgun proteomics. Anal Chem 80:6715–6723

    Article  CAS  Google Scholar 

  • Eshgi A, Cullen PA, Cowen L, Zuerner RL, Cameron CE (2009) Global proteome analysis of Leptospira interrogans. J Prot Res 8:4564–4578

    Article  Google Scholar 

  • Feist AM, Palsson BØ (2008) The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. Nat Biotechnol 26:659–667

    Article  CAS  Google Scholar 

  • Fischer F, Poetsch A (2006) Protein cleavage strategies for an improved analysis of the membrane proteome. Proteome Sci 4:2

    Article  Google Scholar 

  • Forner F, Foster LJ, Campanaro S, Valle G, Mann M (2006) Quantitative proteomic comparison of rat mitochondria from muscle, heart, and liver. Mol Cell Proteomics 5:144–156

    Google Scholar 

  • Fränzel B, Fischer F, Trötschel C, Poetsch A, Wolters D (2009) The two-phase partitioning system—a powerful technique to purify integral membrane proteins of Corynebacterium glutamicum for quantitative shotgun analysis. Proteomics 9:2263–2272

    Article  Google Scholar 

  • Fränzel B, Poetsch A, Trötschel C, Persicke M, Kalinoswski J, Wolters DA, Andreas D (2010) Quantitative proteomic overview on the Corynebacterium glutamicum L-lysine producing strain DM1730. J Proteomics 73:2336–2353

    Article  Google Scholar 

  • Fu X, Gharib SA, Gren PS, Aitken ML, Frazer DA, Park DR, Vaisar T, Heinecke JW (2008) Spectral index for assessment of differential protein expression in shotgun proteomics. J Proteome Res 7:845–854

    Article  CAS  Google Scholar 

  • Gerber SA, Rush J, Stemman O, Kirschner MW, Gygi SP (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc Natl Acad Sci USA 100:6940–6945

    Article  CAS  Google Scholar 

  • Griffin NM, Yu J, Long F, Oh P, Shore S, Li Y, Koziol JA, Schnitzer JE (2009) Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis. Nat Biotechnol 28:83–89

    Article  Google Scholar 

  • Gygi SP, Rist B, Gerber SA, Turecek F, Gelb MH, Aebersold R (1999) Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat Biotechnol 17:994–999

    Article  CAS  Google Scholar 

  • Hahne H, Wolff S, Hecker M, Becher D (2008) From complementarity to comprehensiveness—targeting the membrane proteome of growing Bacillus subtilis by divergent approaches. Proteomics 8:4123–4136

    Article  CAS  Google Scholar 

  • Hecker M, Engelmann S, Cordwell SJ (2003) Proteomics of Staphylococcus aureus—current state and future challenges. J Chromatogr 787:179–195

    Article  CAS  Google Scholar 

  • Hendrickson EL, Beck DAC, Wang TS, Lidstrom ME, Hackett M, Chistoserdova L (2010) Expressed genome of Methylobacillus flagellatus as defined through comprehensive proteomics and new insights into methylotrophy. J Bacteriol 192:4859–4867

    Article  CAS  Google Scholar 

  • Hu Q, Noll RJ, Li H, Makarov A, Hardman M, Graham Cooks R (2005) The Orbitrap: a new mass spectrometer. J Mass Spectrom 40:430–443

    Article  CAS  Google Scholar 

  • Ishihama Y, Oda Y, Tabata T, Sato T, Nagasu T, Rappsilber J, Mann M (2005) Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol Cell Proteomics 4:1265–1272

    Article  CAS  Google Scholar 

  • Ishihama Y, Schmidt T, Rappsilber J, Mann M, Ulrich Hartl F, Kerner MJ, Frishman D (2008) Protein abundance profiling of the Escherichia coli cytosol. BMC Genomics 9:102

    Article  Google Scholar 

  • Jabbour RE, Deshpande SV, Wade MM, Stanford MF, Wick CH, Zulich AW, Skowronski EW, Snyder AP (2010) Double-blind characterization of non-genome-sequenced bacteria by mass spectrometry-based proteomics. Appl Environ Microbiol 76:3637–3644

    Article  CAS  Google Scholar 

  • Kanehisa M, Goto S, SK S, Nakaya A (2002) The KEGG databases at GenomeNet. Nucleic Acids Res 30:42–46

    Article  CAS  Google Scholar 

  • Karp D, Ouzounis CA, Moore-Kochlacs C, Goldovsky L, Kaipa P, Ahren D, Tsoka S, Darzentas N, Kunin V, Lopez-Bigas N (2005) Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res 19:6083–6089

    Article  Google Scholar 

  • Keseler IM, Bonavides-Martinez C, Collado-Vides J, Gama-Castro S, Gunsalus RP, Johnson DA, Krummenacker M, Nolan LM, Paley S, Paulsen IT, Peralta-Gil M, Santos-Zavaleta A, Shearer AG, Karp PD (2009) EcoCyc: a comprehensive view of Escherichia coli biology. Nucleic Acids Res 37:D464–D470

    Article  CAS  Google Scholar 

  • Lee JM, Gianchandani EP, Papin JA (2006) Flux balance analysis in the era of metabolomics. Brief Bioinform 7:140–150

    Article  Google Scholar 

  • Luche S, Santoni V, Rabilloud T (2003) Evaluation of nonionic and zwitterionic detergents as membrane protein solubilizers in two-dimensional electrophoresis. Proteomics 3:249–253

    Article  CAS  Google Scholar 

  • Lundgren DH, Hwang SI, Wu L, Han DK (2010) Role of spectral counting in quantitative proteomics. Expert Rev Proteomics 7:39–53

    Article  CAS  Google Scholar 

  • Mirgorodskaya OA, Kozmin YP, Titov MI, Korner R, Sonksen CP, Roepstorff P (2000) Quantification of peptides and proteins by matrix-assisted laser desorption/ionization mass spectrometry using (18) O-labeled internal standards. Rapid Commun Mass Spectrom 14:1226–1232

    Article  CAS  Google Scholar 

  • Mitulović G, Mechtler K (2006) HPLC techniques for proteomics analysis—a short overview of latest developments. Brief Funct Genomic Proteomic 5:249–260

    Article  Google Scholar 

  • Natale DA, Arighi CN, Barker WC, Blake J, Chang TC, Hu Z, Liu H, Smith B, Wu CH (2007) Framework for a protein ontology. BMC Bioinform 8(Suppl 9):S1

    Article  Google Scholar 

  • Nesvizhskii AI, Keller A, Kolker E, Aebersold R (2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem 75:4646–4658

    Article  CAS  Google Scholar 

  • Nesvizhskii AI, Vitek O, Aebersold R (2007) Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat Meth 4:787–797

    Article  CAS  Google Scholar 

  • Noirel J, Ow SY, Sanguintti G, Wright PC (2009) Systems biology meets synthetic biology: a case study of the metabolic effects of synthetic rewiring. Mol Biosyst 5:1214–1223

    Article  CAS  Google Scholar 

  • Old WM, Meyer-Arendt K, Aveline-Wolf L, Pierce KG, Mendoza A, Sevinsky JR, Resing KA, Ahn NG (2005) Comparison of label-free methods for quantifying human proteins by shotgun proteomics. Mol Cell Proteomics 4:1487–1502

    Article  CAS  Google Scholar 

  • Ong SE, Blagoev B, Kratchmarova I, Kristensen DB, Steen H, Pandey A, Mann M (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1:376–386

    Article  CAS  Google Scholar 

  • Orchard S, Jones A, Albar JP, Cho SY, Kwon KH, Lee C, Hermjakob H (2010) Tackling quantitation: a report on the annual spring workshop of the HUPO–PSI. Proteomics 10:3062–3066

    Article  CAS  Google Scholar 

  • Orth JD, Thiele I, Palsson BØ (2010) What is flux balance analysis? Nat Biotechnol 28:245–248

    Article  CAS  Google Scholar 

  • Otto A, Bernhardt J, Meyer H, Schaffer M, Herst FA, Siebourg J, Mäder U, Lalk M, Hecker M, Becher D (2010) Systems-wide temporal proteomic profiling in glucose-starved Bacillus subtilis. Nature Comm 1(9):137

    Article  Google Scholar 

  • Pham TV, Piersma SR, Warmoes M, Jimenez CR (2010) On the beta-binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics. Bioinformatics 26:363–369

    Article  CAS  Google Scholar 

  • Prattl JM, Simpson DM, Doherty MK, Rivers J, Gaskell SJ, Beynon RJ (2006) Multiplexed absolute quantification for proteomics using concatenated signature peptides encoded by QconCAT genes. Nat Protocol 1:1029–1043

    Article  Google Scholar 

  • Rappsilber J, Ryder U, Lamond AI, Mann M (2002) Large-scale proteomic analysis of the human spliceosome. Genome Res 12:1231–1245

    Article  CAS  Google Scholar 

  • Rietschel B, Arrey TN, Meyer B, Bornemann S, Schuerken M, Karas M, Poetsch A (2009) Elastase digests: new ammunition for shotgun membrane proteomics. Mol Cell Proteomics 8:1029–1043

    Article  CAS  Google Scholar 

  • Ross PL, Huang YLN, Marchese JN, Williamson B, Parker K, Hattan S, Khainovski N, Pillai S, Dey S, Daniels S, Purkayastha S, Juhasz P, Martin S, Bartlet-Jones M, He F, Jacobson A, Pappin DJ (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3:1154–1169

    Article  CAS  Google Scholar 

  • Sanders SL, Jennings J, Canutescu A, Link AJ, Weil PA (2002) Proteomics of the eukaryotic transcription machinery: identification of proteins associated with components of yeast TFIID by multidimensional mass spectrometry. Mol Cell Biol 22:4723–4738

    Article  CAS  Google Scholar 

  • Shadforth IP, Dunnley PJ, Lilley KS, Bessant C (2005) i-Tracker: for quantitative proteomics using iTRAQ. BMC Genomics 6:145

    Article  Google Scholar 

  • Tyo KEJ, Kocharin K, Nielsen J (2010) Toward design-based engineering of industrial microbes. Curr Opin Microbiol 13:255–262

    Article  CAS  Google Scholar 

  • Williams DA (1976) Improved likelihood ratio test for complete contingency tables. Biometrika 63:33–37

    Article  Google Scholar 

  • Wilmes P, Bond PL (2006) Metaproteomics: studying functional gene expression in microbial ecosystems. Trends Microbiol 14:92–97

    Article  CAS  Google Scholar 

  • Wilmes P, Bowen BP, Thomas BC, Mueller RS, Denef VJ, VerBerkmoes NC, Hettich RL, Northen TR, Banfield JF (2010) Metabolome–proteome differentiation coupled to microbial divergence. MBio 1(5):e00246-10

    Article  Google Scholar 

  • Yates JR, Ruse CI, Nakorchevsky A (2009) Proteomics by mass spectrometry: approaches, advances, and applications. Annu Rev Biomed Eng 11:49–79

    Article  CAS  Google Scholar 

  • Yizhak K, Benyamini T, Liebermeister W, Ruppin E, Shlomi T (2010) Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model. Bioinformatics 26:255–260

    Article  Google Scholar 

  • Zhang B, VerBerkmoes NC, Langston MA, Uberbacher E, Hettich RL, Samatova NF (2006) Detecting differential and correlated protein expression in label-free shotgun proteomics. J Proteome Res 5:2909–2918

    Article  CAS  Google Scholar 

  • Zybailov B, Mosley AL, Sardiu ME, Coleman MK, Florens L, Washburn MP (2006) Statistical analysis of membrane proteome expression changes in Saccharomyces cerevisiae. J Proteome Res 5:2339–2347

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tasmanian Institute of Agricultural Research, School of Agricultural Science, University of Tasmania, College Road, Sandy Bay, 7005, Hobart, Tasmania, Australia

    Bianca Porteus, Chawalit Kocharunchitt, Rolf E. Nilsson, Tom Ross & John P. Bowman

Authors
  1. Bianca Porteus
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chawalit Kocharunchitt
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rolf E. Nilsson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tom Ross
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. John P. Bowman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to John P. Bowman.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Porteus, B., Kocharunchitt, C., Nilsson, R.E. et al. Utility of gel-free, label-free shotgun proteomics approaches to investigate microorganisms. Appl Microbiol Biotechnol 90, 407–416 (2011). https://doi.org/10.1007/s00253-011-3172-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00253-011-3172-z

Keywords

Search

Navigation