Skip to main content
Log in

Predicting stable functional peptides from the intergenic space of E. coli

  • Research Article
  • Published:
Systems and Synthetic Biology

Abstract

Expression of synthetic proteins from intergenic regions of E. coli and their functional association was recently demonstrated (Dhar et al. in J Biol Eng 3:2, 2009. doi:10.1186/1754-1611-3-2). This gave birth to the question: if one can make ‘user-defined’ genes from non-coding genome—how big is the artificially translatable genome? (Dinger et al. in PLoS Comput Biol 4, 2008; Frith et al. in RNA Biol 3(1):40–48, 2006a; Frith et al. in PLoS Genet 2(4):e52, 2006b). To answer this question, we performed a bioinformatics study of all reported E. coli intergenic sequences, in search of novel peptides and proteins, unexpressed by nature. Overall, 2500 E. coli intergenic sequences were computationally translated into ‘protein sequence equivalents’ and matched against all known proteins. Sequences that did not show any resemblance were used for building a comprehensive profile in terms of their structure, function, localization, interactions, stability so on. A total of 362 protein sequences showed evidence of stable tertiary conformations encoded by the intergenic sequences of E. coli genome. Experimental studies are underway to confirm some of the key predictions. This study points to a vast untapped repository of functional molecules lying undiscovered in the non-expressed genome of various organisms.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Cherian BS, Nair AS (2010) Protein location prediction using atomic composition and global features of the amino acid sequence. Biochem Biophys Res Commun 391:1670–1674

    Article  CAS  PubMed  Google Scholar 

  • Dhar PK, Thwin CS, Tun K, Tsumoto Y, Maurer-Stroh S, Eisenhaber F, Surana U (2009) Synthesizing non-natural parts from natural genomic template. J Biol Eng 3:2. doi:10.1186/1754-1611-3-2

    Article  PubMed Central  PubMed  Google Scholar 

  • Dinger ME, Pang KC, Mercer TR, Mattick JS (2008) Differentiating protein-coding and noncoding RNA: challenges and ambiguities. PLoS Comput Biol 4(11):e1000176

  • Dosztanyi Z, Magyar C, Tusnady G, Simon I (2003) SCide: identification of stabilization centers in proteins. Bioinformatics 19:899–900

    Article  CAS  PubMed  Google Scholar 

  • Frith MC, Bailey TL, Kasukawa T, Mignone F, Kummerfeld SK, Madera M, Sunkara S et al (2006a) Discrimination of non-protein-coding transcripts from protein-coding mRNA. RNA Biol 3(1):40–48

    Article  CAS  PubMed  Google Scholar 

  • Frith MC, Forrest AR, Nourbakhsh E, Pang KC, Kai C, Kawai J, Carninci P et al (2006b) The abundance of short proteins in the mammalian proteome. PLoS Genet 2(4):e52

    Article  PubMed Central  PubMed  Google Scholar 

  • Gallivan JP, Dougherty DA (1999) Cation-pi interactions in structural biology. Proc Natl Acad Sci USA 96:9459

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. The Proteomics Protocols Handbook. Humana Press, New York, pp 571–607

    Book  Google Scholar 

  • Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-Pdb viewer: an environment for comparative protein modeling. Electrophoresis 18:2714–2723

    Article  CAS  PubMed  Google Scholar 

  • Harrison RS, Shepherd NE, Hoang HN, Ruiz-Gómez G, Hill TA, Driver RW, Desai VS et al (2010) Downsizing human, bacterial, and viral proteins to short water-stable alpha helices that maintain biological potency. Proc Natl Acad Sci USA 107(26):11686–11691

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Jensen LJ, Gupta R, Blom N, Devos D, Tamames J, Kesmir C, Nielsen H, Stærfeldt HH, Rapacki K, Workman C, Andersen CAF, Knudsen S, Krogh A, Valencia A, Brunak S (2002) Ab initio prediction of human orphan protein function from post-translational modifications and localization features. J Mol Biol 319:1257–1265

    Article  CAS  PubMed  Google Scholar 

  • Kageyama Y, Kondo T, Hashimoto Y (2011) Coding vs non-coding: translatability of short ORFs found in putative non-coding transcripts. Biochimie 93:1981–1986

    Article  CAS  PubMed  Google Scholar 

  • Kondo T, Plaza S, Zanet J, Benrabah E, Valenti P, Hashimoto Y, Kobayashi S, Payre F, Kageyama Y (2010) Small peptides switch the transcriptional activity of Shavenbaby during Drosophila embryogenesis. Science 5989:336–339

    Article  Google Scholar 

  • Powers J-PS, Hancock REW (2003) The relationship between peptide structure and antibacterial activity. Peptides 24:1681–1691

    Article  CAS  PubMed  Google Scholar 

  • Ramanathan K, Shanthi V, Rajasekaran R, Sudandiradoss C, Doss CGP, Sethumadhavan R (2011) Predicting therapeutic template by evaluating the structural stability of anti-cancer peptides: a computational approach. Int J Pept Res Ther 17(1):31–38

    Article  CAS  Google Scholar 

  • Tina KG, Bhadra R, Srinivasan N (2007) PIC: protein interactions calculator. Nucl Acids Res 35:W473–W476

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Vriend G (1990) WHAT IF: a molecular modeling and drug design program. J Mol Graph 8:52–56

    Article  CAS  PubMed  Google Scholar 

  • Yu CS, Chen YC, Lu CH, Hwang JK (2006) Prediction of protein subcellular localization. Prot Struct Funct Bioinform 64:643–651

    Article  CAS  Google Scholar 

  • Zhang Y (2008) I-TASSER server for protein 3D structure prediction. BMC Bioinform 9:40

    Article  Google Scholar 

Download references

Acknowledgments

We sincerely thank the State Inter-University Centre of Excellence in Bioinformatics (SIUCEB), University of Kerala for the funding provided during this work.

Conflict of interest

The authors declare that they have no conflict of interests.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Achuthsankar S. Nair.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thomas, V., Raj, N., Varughese, D. et al. Predicting stable functional peptides from the intergenic space of E. coli . Syst Synth Biol 9, 135–140 (2015). https://doi.org/10.1007/s11693-015-9172-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11693-015-9172-z

Keywords

Navigation