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Comparison of Different Signal Sequences to Use for Periplasmic Over-Expression of Buforin I in Escherichia coli: An In Silico Study

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Abstract

Computational prediction of signal peptides is one of the most important steps in genetic engineering experiments. The periplasmic expression cause the reducing in the inherent destructive behavior of Bofurin I against its host and also reducing its susceptibility to proteolytic degradation. In order to predict the best signal peptides for expression of Buforin I in E. coli, 103 signal sequences were retired from signal peptide databases. Since the purpose of this study was to introduce the optimal signal peptides for periplasmic expression, first, sub-cellular localization site of signal peptides was analyzed. Then, n, h, and c regions of signal peptide, signal peptide probability and physico-chemical features were investigated. Base on the results, MalE, hofQ, papK, ugpB, zraP, and sfmC were introduced as the best signal peptides. For increasing the half-life of mRNA and the increasing the stability of the mRNA against exonuclease activity, secondary structures of mRNA including Shine-Dalgarno, untranslated region of ompA, start codon, signal peptide and sequences of Buforin I were analyzed. Based on the total free energy pilot evaluated and mRNA conformations, papK seemed more appropriate than the rest of the signal peptides. The obtained result of this study can be used for design the periplasmic expression constructs.

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Abbreviations

SP:

Signal peptide

SS:

Signal sequence

AMP:

Anti-microbial peptide

NCB:

National Center of Biotechnology Information

RNA:

Ribonucleic acid

GRAVY:

Grand average of hydropathicity

PI:

Isoelectric point

CSP:

Cleavage site probability

PCP:

Predicted cleavage position

PCP:

Predicted cleavage location

References

  • Ali F, Yao Z, Li W, Sun L, Lin W, Lin X (2018) In-silico prediction and modeling of the quorum sensing LuxS protein and inhibition of AI-2 biosynthesis in Aeromonas hydrophila. Molecules 23(10):2627–2649

    PubMed Central  Google Scholar 

  • Arnold T, Yu J, Belasco JG (1998) mRNA stabilization by the ompA 5′ untranslated region: two protective elements hinder distinct pathways for mRNA degradation. RNA 4(3):319–330

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bagos PG, Nikolaou EP, Liakopoulos TD, Tsirigos KD (2010) Combined prediction of Tat and Sec signal peptides with hidden Markov models. Bioinformatics 26(22):2811–2817

    CAS  PubMed  Google Scholar 

  • Baltzer SA, Brown MH (2011) Antimicrobial peptides—promising alternatives to conventional antibiotics. J Mol Microbiol Biotechnol 20(4):228–235

    CAS  PubMed  Google Scholar 

  • Burdukiewicz M, Sobczyk P, Chilimoniuk J, Gagat P, Mackiewicz P (2018) Prediction of signal peptides in proteins from Malaria Parasites. Int J Mol Sci 19(12):3709–3725

    PubMed Central  Google Scholar 

  • Choi JH, Lee SY (2004) Secretory and extracellular production of recombinant proteins using Escherichia coli. Appl Microbiol Biotechnol 64(5):625–635

    CAS  PubMed  Google Scholar 

  • Choo KH, Tan TW, Ranganathan S (2005) SPdb–a signal peptide database. BMC Bioinformatics 6:249–249

    PubMed  PubMed Central  Google Scholar 

  • Daneshmand A, Kermanshahi H, Sekhavati MH, Javadmanesh A, Ahmadian M (2019) Antimicrobial peptide, cLF36, affects performance and intestinal morphology, microflora, junctional proteins, and immune cells in broilers challenged with E. coli. Sci Rep 9(1):1–9

    CAS  Google Scholar 

  • Darvishi F, Zarei A, Madzak C (2018) In silico and in vivo analysis of signal peptides effect on recombinant glucose oxidase production in nonconventional yeast Yarrowia lipolytica. World J Microbiol Biotechnol 34(9):128–132

    PubMed  Google Scholar 

  • Esposito D, Chatterjee DK (2006) Enhancement of soluble protein expression through the use of fusion tags. Curr Opin Biotechnol 17(4):353–358

    CAS  PubMed  Google Scholar 

  • Forouharmehr A, Nassiri M, Ghovvati S, Javadmanesh A (2018) Evaluation of different signal peptides for secretory production of recombinant bovine pancreatic ribonuclease A in gram negative bacterial system: an in silico study. Curr Proteomics 15(1):24–33

    CAS  Google Scholar 

  • Freiherr von Roman M, Koller A, von Rüden D, Berensmeier S (2014) Improved extracellular expression and purification of recombinant Staphylococcus aureus protein A. Protein Expr Purif 93:87–92

    CAS  PubMed  Google Scholar 

  • Freudl R (2018) Signal peptides for recombinant protein secretion in bacterial expression systems. Microb Cell Fact 17(1):52–62

    PubMed  PubMed Central  Google Scholar 

  • Gardy JL, Laird MR, Chen F, Rey S, Walsh C, Ester M, Brinkman FS (2004) PSORTb v. 2.0: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis. Bioinformatics 21(5):617–623

    PubMed  Google Scholar 

  • Gasteiger EHC, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. In: JM (ed) The proteomics protocols handbook. Humana Press, Totowa, pp 571–607

    Google Scholar 

  • Ghovvati S, Pezeshkian Z, Mirhoseini SZ (2018) In silico analysis of different signal peptides to discover a panel of appropriate signal peptides for secretory production of Interferon-beta 1b in Escherichia coli. Acta Biochim Pol 65(4):521–534

    CAS  PubMed  Google Scholar 

  • Godbey WT (2014) Chapter 4—genes: the blueprints for proteins. In: Godbey WT (ed) An introduction to biotechnology. Woodhead Publishing, Sawston, pp 65–105

    Google Scholar 

  • Han S, Machhi S, Berge M, Xi G, Linke T, Schoner R (2017) Novel signal peptides improve the secretion of recombinant Staphylococcus aureus Alpha toxin H35L in Escherichia coli. AMB Express 7(1):93–107

    PubMed  PubMed Central  Google Scholar 

  • Hansen MJ, Chen LH, Fejzo ML, Beiasco JG (1994) The ompA 5′ untranslated region impedes a major pathway for mRNA degradation in Escherichia coli. Mol Microbiol 12(5):707–716

    CAS  PubMed  Google Scholar 

  • Hebditch M, Carballo-Amador MA, Charonis S, Curtis R, Warwicker J (2017) Protein-Sol: a web tool for predicting protein solubility from sequence. Bioinformatics (Oxford, England) 33(19):3098–3100

    CAS  Google Scholar 

  • Hofacker IL (2003) Vienna RNA secondary structure server. Nucleic Acids Res 31(13):3429–3431

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hoffmann F, van den Heuvel J, Zidek N, Rinas U (2004) Minimizing inclusion body formation during recombinant protein production in Escherichia coli at bench and pilot plant scale. Enzyme Microb Technol 34(3–4):235–241

    CAS  Google Scholar 

  • Jahandar MH, Forouharmehr A (2018) Optimization of human serum albumin periplasmic localization in Escherichia coli using in silico evaluation of different signal peptides. Int J Pept Res Ther 25(2):635–643

    Google Scholar 

  • Jeiranikhameneh M, Moshiri F, Keyhan Falasafi S, Zomorodipour A (2017) Designing signal peptides for efficient periplasmic expression of human growth hormone in Escherichia coli. J Microbiol Biotechnol 27(11):1999–2009

    CAS  PubMed  Google Scholar 

  • Johnson TL, Abendroth J, Hol WGJ, Sandkvist M (2006) Type II secretion: from structure to function. FEMS Microbiol Lett 255(2):175–186

    CAS  PubMed  Google Scholar 

  • Käll L, Krogh A, Sonnhammer ELL (2004) A combined transmembrane topology and signal peptide prediction method. J Mol Biol 338(5):1027–1036

    PubMed  Google Scholar 

  • Lorenz R, Wolfinger MT, Tanzer A, Hofacker IL (2016) Predicting RNA secondary structures from sequence and probing data. Methods 103:86–98

    CAS  PubMed  Google Scholar 

  • Mackie GA (2012) RNase E: at the interface of bacterial RNA processing and decay. Nat Rev Microbiol 11(1):45–57

    Google Scholar 

  • Magnan CN, Randall A, Baldi P (2009) SOLpro: accurate sequence-based prediction of protein solubility. Bioinformatics 25(17):2200–2207

    CAS  PubMed  Google Scholar 

  • Mergulhao F, Summers DK, Monteiro GA (2005) Recombinant protein secretion in Escherichia coli. Biotechnol Adv 23(3):177–202

    CAS  PubMed  Google Scholar 

  • Nazifi N, Tahmoorespur M, Sekhavati MH, Haghparast A, Behroozikhah MA (2019) Assessment of signal peptides to optimize interleukin 2 (IL-2) folding and expression. Curr Proteomics 16(3):188–198

    CAS  Google Scholar 

  • Negahdaripour M, Nezafat N, Hajighahramani N, Rahmat Abadi S, Morowvat SH, Mohammad Ghasemi Y (2017) In silico study of different signal peptides for secretory production of interleukin-11 in Escherichia coli. Curr Proteomics 14(2):112–121

    CAS  Google Scholar 

  • Ortega S, García JL, Zazo M, Varela J, Muñoz-Willery I, Cuevas P, Giménez-Gallego G (1992) Single-step purification on DEAE–Sephacel of recombinant polypeptides produced in Escherichia Coli. Bio/Technology 10(7):795–798

    CAS  Google Scholar 

  • Paladin L, Piovesan D, Tosatto SC (2017) SODA: prediction of protein solubility from disorder and aggregation propensity. Nucleic Acids Res 45(W1):W236–W240

    CAS  PubMed  PubMed Central  Google Scholar 

  • Park CB, Kim MS, Kim SC (1996) A novel antimicrobial peptide from Bufo bufo gargarizans. Biochem Biophys Res Commun 218(1):408–413

    CAS  PubMed  Google Scholar 

  • Pirkhezranian Z, Tanhaeian A, Mirzaii M, Sekhavati MH (2019) Expression of Enterocin-P in HEK platform: evaluation of its cytotoxic effects on cancer cell lines and its potency to interact with cell-surface glycosaminoglycan by molecular modeling. Int J Pept Res Ther. https://doi.org/10.1007/s10989-019-09956-7

    Article  Google Scholar 

  • Pirkhezranian Z, Tahmoorespur M, Monhemi H, Sekhavati MH (2020) Computational peptide engineering approach for selection the best engendered camel lactoferrin-derive peptide with potency to interact with DNA. Int J Pept Res Ther. https://doi.org/10.1007/s10989-019-10012-7

    Article  Google Scholar 

  • Ringquist S, Shinedling S, Barrick D, Green L, Binkley J, Stormo GD, Gold L (1992) Translation initiation in Escherichia coli: sequences within the ribosome-binding site. Mol Microbiol 6(9):1219–1229

    CAS  PubMed  Google Scholar 

  • Shen H-B, Chou K-C (2010) Gneg-mPLoc: a top-down strategy to enhance the quality of predicting subcellular localization of Gram-negative bacterial proteins. J Theor Biol 264(2):326–333

    CAS  PubMed  Google Scholar 

  • Shokri A, Sandén A, Larsson G (2003) Cell and process design for targeting of recombinant protein into the culture medium of Escherichia coli. Appl Microbiol Biotechnol 60(6):654–664

    CAS  PubMed  Google Scholar 

  • Sletta H, Tøndervik A, Hakvåg S, Aune TV, Nedal A, Aune R, Evensen G, Valla S, Ellingsen T, Brautaset T (2007) The presence of N-terminal secretion signal sequences leads to strong stimulation of the total expression levels of three tested medically important proteins during high-cell-density cultivations of Escherichia coli. Appl Environ Microbiol 73(3):906–912

    CAS  PubMed  Google Scholar 

  • Tahmoorespur M, Azghandi M, Javadmanesh A, Meshkat Z, Sekhavati MH (2019) A novel chimeric anti-HCV peptide derived from camel lactoferrin and molecular level insight on its interaction with E2. Int J Pept Res Ther. https://doi.org/10.1007/s10989-019-09972-7

    Article  Google Scholar 

  • Takemori D, Yoshino K, Eba C, Nakano H, Iwasaki Y (2012) Extracellular production of phospholipase A2 from Streptomyces violaceoruber by recombinant Escherichia coli. Protein Expr Purif 81(2):145–150

    CAS  PubMed  Google Scholar 

  • Tanhaeian A, Ahmadi FS, Sekhavati MH, Mamarabadi M (2018) Expression and purification of the main component contained in camel milk and its antimicrobial activities against bacterial plant pathogens. Probiotics Antimicrob Proteins 10(4):787–793

    CAS  PubMed  Google Scholar 

  • Vahedi F, Nassiri M, Ghovvati S, Javadmanesh A (2018) Evaluation of different signal peptides using bioinformatics tools to express recombinant erythropoietin in mammalian cells. Int J Pept Res Ther 25(3):989–995

    Google Scholar 

  • Viratyosin W, Ingsriswang S, Pacharawongsakda E, Palittapongarnpim P (2008) Genome-wide subcellular localization of putative outer membrane and extracellular proteins in Leptospira interrogans serovar Lai genome using bioinformatics approaches. BMC Genomics 9(1):181–196

    PubMed  PubMed Central  Google Scholar 

  • Yarabbi H, Mortazavi SA, Yavarmanesh M, Javadmanesh A (2019) In silico study of different signal peptides to express recombinant glutamate decarboxylase in the outer membrane of Escherichia coli. Int J Pept Res Ther. https://doi.org/10.1007/s10989-019-09986-1

    Article  Google Scholar 

  • Yu K, Lin L, Hu S, Huang J, Mei L (2012) C-terminal truncation of glutamate decarboxylase from Lactobacillus brevis CGMCC 1306 extends its activity toward near-neutral pH. Enzyme Microb Technol 50(4–5):263–269

    CAS  PubMed  Google Scholar 

  • Zamani M, Nezafat N, Negahdaripour M, Dabbagh F, Ghasemi Y (2015) In silico evaluation of different signal peptides for the secretory production of human growth hormone in E. coli. Int J Pept Res Ther 21(3):261–268

    CAS  Google Scholar 

  • Zavialov AV, Batchikova NV, Korpela T, Petrovskaya LE, Korobko VG, Kersley J, MacIntyre S, Zav'yalov VP (2001) Secretion of recombinant proteins via the chaperone/usher pathway in Escherichia coli. Appl Environ Microbiol 67(4):1805–1814

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang W, Lu J, Zhang S, Liu L, Pang X, Lv J (2018a) Development an effective system to expression recombinant protein in E. coli via comparison and optimization of signal peptides: expression of Pseudomonas fluorescens BJ-10 thermostable lipase as case study. Microb Cell Factor 17(1):50

    CAS  Google Scholar 

  • Zhang W, Lu J, Zhang S, Liu L, Pang X, Lv J (2018b) Development an effective system to expression recombinant protein in E. coli via comparison and optimization of signal peptides: expression of Pseudomonas fluorescens BJ-10 thermostable lipase as case study. Microbial Cell Factor 17(1):50–62

    CAS  Google Scholar 

  • Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31(13):3406–3415

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This study was supported by the Ferdowsi University of Mashhad (Grant No. 3/48253) and Iran National Science Foundation: INSF (Grant No. 97011516).

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Authors and Affiliations

  1. Department of Food Science and Technology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

    Sahar Roshanak, Farideh Tabatabaei Yazdi & Fakhri Shahidi

  2. Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

    Ali Javadmanesh

  3. Department of Pharmaceutical Nanotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran

    Jebrail Movaffagh

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  1. Sahar Roshanak
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  2. Farideh Tabatabaei Yazdi
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  3. Fakhri Shahidi
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Correspondence to Farideh Tabatabaei Yazdi or Fakhri Shahidi.

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Roshanak, S., Tabatabaei Yazdi, F., Shahidi, F. et al. Comparison of Different Signal Sequences to Use for Periplasmic Over-Expression of Buforin I in Escherichia coli: An In Silico Study. Int J Pept Res Ther 26, 2495–2504 (2020). https://doi.org/10.1007/s10989-020-10042-6

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