Skip to main content

Advertisement

Log in

Evaluating the effect of codon optimization on expression of bar gene in transgenic tobacco plants

  • Original Article
  • Published:
Journal of Plant Biochemistry and Biotechnology Aims and scope Submit manuscript

Abstract

Information of codon usage bias has been used for modifying genes for improved expression in heterologous systems. Codon modifications are carried out using the species-specific codon usage so that they reflect the codon usage pattern of the host, without modifying the amino acid sequence of the encoded protein. In the present study we analyzed the effect of codon optimization on the expression of the bacterial gene bar in tobacco. In order to identify the percentage of optimal codons needed to achieve high levels of protein expression, bar genes with different percentage and placement of optimal codons were analyzed in transgenic tobacco lines. It was observed that there was no gain in bar protein expression when the percentage of optimal codons was increased from 63.9% (as observed in the wild type bar gene) to 93.9%. However, reducing the percentage of optimal codons to 54.0 led to a drop in the levels of the bar protein. Further, in silico analysis was also carried out in ~ 4500 genes present on chromosome 2 of Arabidopsis thaliana to study the distribution of optimal codons. It was observed that majority (88%) of the genes have 30–50% of optimal codons and none of the gene was found to have more than 80% of optimal codons. The present study showed that there may not be a one-to-one correlation between the percentage of optimal codons and the expression levels of the transgene. A certain percentage of optimal codons is probably enough to achieve high levels of transgene expression. Any increase in the percentage of optimal codons beyond this level may not necessarily lead to any further improvement in expression.

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
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

CUB:

Codon usage bias

PAT:

Phosphinothricin acetyl transferase

PPT:

Phosphinothricin

RSCU:

Relative synonymous codon usage

URM:

Upstream regulatory module

CUTG:

Codon usage tabulated from GenBank

References

  • Agarwal P, Garg V, Gautam T, Pillai B, Kanoria S, Burma PK (2014) A study on the influence of different promoter and 5′UTR (URM) cassettes from Arabidopsis thaliana on the expression level of the reporter gene β glucuronidase in tobacco and cotton. Transgenic Res 23(2):351–363. https://doi.org/10.1007/s11248-013-9757-9

    Article  CAS  PubMed  Google Scholar 

  • Bai J, Swartz DJ, Protasevich II, Brouillette CG, Harrell PM, Hildebrandt E, Gasser B, Mattanovich D, Ward A, Chang G, Urbatsch IL (2011) A gene optimization strategy that enhances production of fully functional P-glycoprotein in Pichia pastoris. PLoS ONE 6(8):e22577

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Batard Y, Hehn A, Nedelkina S, Schalk M, Pallett K, Schaller H, Werck-Reichhart D (2000) Increasing expression of P450 and P450-reductase proteins from monocots in heterologous systems. Arch Biochem Biophys 379(1):161–169

    Article  CAS  PubMed  Google Scholar 

  • Bhullar S, Chakravarthy S, Advani S, Datta S, Pental D, Burma PK (2003) Strategies for development of functionally equivalent promoters with minimum sequence homology for transgene expression in plants: cis-elements in a novel DNA context versus domain swapping. Plant Physiol 132:988–998. https://doi.org/10.1104/pp.103.020602

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bhullar S, Chakravarthy S, Pental D, Burma PK (2009) Analysis of promoter activity in transgenic plants by normalizing expression with a reference gene: anomalies due to the influence of the test promoter on the reference promoter. J Biosci 34:953–962

    Article  CAS  PubMed  Google Scholar 

  • Biemelt S, Sonnewald U, Gaimbacher P, Willmitzer L, Muller M (2003) Production of human papillomavirus type 16 viral-like particles in transgenic plants. J Virol 77:9211–9220

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–254

    Article  CAS  PubMed  Google Scholar 

  • Buchan JR, Stansfield I (2007) Halting a cellular production line: responses to ribosomal pausing during translation Biol. Cell 99:475–487

    CAS  Google Scholar 

  • Chartier M, Gaudreault F, Najmanovich R (2012) Large-scale analysis of conserved rare codon clusters suggests an involvement in co-translational molecular recognition events. Bioinformatics 28:1438–1445. https://doi.org/10.1093/bioinformatics/bts149

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Collins K, Gandhi L (1998) The reverse transcriptase component of the Tetrahymena telomerase ribonucleoprotein complex. Proc Natl Acad Sci USA 95(15):8485–8490

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cormack BP, Bertram G, Egerton M, Gow NA, Falkow S, Brown AJ (1998) Yeast-enhanced green fluorescent protein (yEGFP)a reporter of gene expression in Candida albicans. Microbiology 143(Pt 2):303–311

    Google Scholar 

  • Desai PN, Shrivastava N, Padh H (2010) Production of heterologous proteins in plants: strategies for optimal expression. Biotechnol Adv 28:427–435. https://doi.org/10.1016/j.biotechadv.2010.01.005

    Article  CAS  PubMed  Google Scholar 

  • Duret L (2000) tRNA gene number and codon usage in the C. elegans genome are coadapted for optimal translation of highly expressed genes. Trends Genet 16:287–289

    Article  CAS  PubMed  Google Scholar 

  • Duret L, Mouchiroud D (1999) Expression pattern and surprisingly, gene length shape codon usage in Caenorhabditis, Drosophila, and Arabidopsis. Proc Natl Acad Sci 96:4482–4487

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gallie DR (1993) Posttranscriptional regulation of gene expression in plants. Annu Rev Plant Physiol Plant Mol Biol 44:77–105

    Article  CAS  Google Scholar 

  • Gao F, Li Y, Decker JM, Peyerl FW, Bibollet-Ruche F, Rodenburg CM, Chen Y, Shaw DR, Allen S, Musonda R, Shaw GM, Zajac AJ, Letvin N, Hahn BH (2003) Codon usage optimization of HIV type 1 subtype C gag, pol, env, and nef genes: in vitro expression and immune responses in DNA-vaccinated mice. AIDS Res Hum Retrovir 19(9):817–823

    Article  CAS  PubMed  Google Scholar 

  • Geyer B, Fletcher S, Griffin T, Lopker M, Soreq H, Mor T (2007) Translational control of recombinant human acetylcholinesterase accumulation in plants. BMC Biotechnol 7:27

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Geyer BC, Kannan L, Cherni I, Woods RR, Soreq H, Mor TS (2010) Transgenic plants as a source for the bioscavenging enzyme, human butyrylcholinesterase. Plant Biotechnol J 8:873–886

    Article  CAS  PubMed  Google Scholar 

  • Gustafsson C, Govindarajan S, Minshull J (2004) Codon bias and heterologous protein expression. Trends Biotechnol 22:346–353

    Article  CAS  PubMed  Google Scholar 

  • Gustafsson C, Minshull J, Govindarajan S, Ness J, Villalobos A, Welch M (2012) Engineering genes for predictable protein expression. Protein Expr Purif 83:37–46

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hamada A, Yamaguchi K, Ohnishi N, Harada M, Nikumaru S, Honda H (2005) High-level production of yeast (Schwanniomyces occidentalis) phytase in transgenic rice plants by a combination of signal sequence and codon modification of the phytase gene. Plant Biotechnol J 3(1):43–55

    Article  CAS  PubMed  Google Scholar 

  • Hu X, Shi Q, Yang T, Jackowski G (1996) Specific replacement of consecutive AGG codons results in high-level expression of human cardiac troponin T in Escherichia coli. Protein Expr Purif 7:289–293

    Article  CAS  PubMed  Google Scholar 

  • Ikemura T (1981a) Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: a proposal for a synonymous codon choice that is optimal for the E. coli system. J Mol Biol 151:389–409

    Article  CAS  PubMed  Google Scholar 

  • Ikemura T (1981b) Correlation between the abundance of Escherichia coli transfer RNAs and theoccurrence of the respective codons of its protein genes. J Mol Biol 146:1–21

    Article  CAS  PubMed  Google Scholar 

  • Ikemura T (1982) Correlation between the abundance of yeast tRNAs and the occurrence of the respective codons in protein genes. Differences in synonymous codon choice patterns of yeast and Escherichia coli with reference to the abundance of isoaccepting transfer RNAs. J Mol Biol 158:573–597

    Article  CAS  PubMed  Google Scholar 

  • Ikemura T (1985) Codon usage and transfer-RNA content in unicellular and multicellular organisms. Mol Biol Evol 2:13–34

    CAS  PubMed  Google Scholar 

  • Itakura K, Hirose T, Crea R, Riggs AD, Heyneker HL, Bolivar F, Boyer HW (1977) Expression in Escherichia coli of a chemically synthesized gene for the hormone somatostatin. Science 198:1056–1063

    Article  CAS  PubMed  Google Scholar 

  • Jackson MA, Sternes PR, Mudge SR, Graham MW, Birch RG (2014) Design rules for efficient expression in plants. Plant Biotechnol J. https://doi.org/10.1111/pbi.12197

    Article  PubMed  Google Scholar 

  • Jaganath A (1999) Modification and synthesis of barstar and bar genes and development of barnase/barstar lines in Brassica juncea L. for hybrid seed production. Ph.D. Thesis, University of Delhi

  • Kanaya S, Yamada Y, Kinouchi M, Kudo Y, Ikemura T (2001) Codon Usage and tRNA genes in eukaryotes: correlation of codon usage diversity with translation efficiency and with CG-dinucleotide usage as assessed by multivariate analysis. J Mol Evol 53:290–298

    Article  CAS  PubMed  Google Scholar 

  • Kanoria S, Burma PK (2012) A 28 nt long synthetic 5′UTR (synJ) as an enhancer of transgene expression in dicotyledonous plants. BMC Biotechnol 12:85. https://doi.org/10.1186/1472-6750-12-85

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kimchi-Sarfaty C, Oh JM, Kim IW, Sauna ZE, Calcagno AM, Ambudkar SV, Gottesman MM (2007) A “silent” polymorphism in the MDR1 gene changes substrate specificity. Science 315:525–528

    Article  CAS  PubMed  Google Scholar 

  • Kudla G, Murray AW, Tollervey D, Plotkin JB (2009) Coding-sequence determinants of gene expression in Escherichia coli. Science 324:255–258. https://doi.org/10.1126/science.1170160

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kumar S, Timko MP (2004) Enhanced tissue-specific expression of the herbicide resistance bar gene in transgenic cotton (Gossypium hirsutum L cv. Coker 310FR) using the Arabidopsis rbcS ats1A promoter. Plant Biotechnol J 21:251–259

    Article  CAS  Google Scholar 

  • Laguía-Becher M, Martín V, Kraemer M, Corigliano M, Yacono ML, Goldman A, Clemente M (2010) Effect of codon optimization and subcellular targeting on Toxoplasma gondii antigen SAG1expression in tobacco leaves to use in subcutaneous and oral immunization in mice. BMC Biotechnol 10:52

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li XQ, Wei JZ, Tan A, Aroian RV (2007) Resistance to rootknot nematode in tomato roots expressing a nematicidal Bacillus thuringiensis crystal protein. Plant Biotechnol J 5:455–464

    Article  CAS  PubMed  Google Scholar 

  • Maclean J, Koekemoer M, Olivier AJ, Stewart D, Hitzeroth II, Rademacher T, Fischer R, Williamson A-L, Rybicki EP (2007) Optimization of human papillomavirus type 16 (HPV-16) L1 expression in plants: comparison of the suitability of different HPV-16 L1 gene variants and different cell-compartment localization. J Gen Virol 88:1460–1469

    Article  CAS  PubMed  Google Scholar 

  • Mehra S (1999) Development and molecular analysis of herbicide resistant transgenics in Brassica juncea L. containing wild type and modified bar genes. Ph.D. Thesis, University of Delhi

  • Mehra S, Pareek A, Bandyopadhyay P, Sharma P, Burma PK, Pental D (2000) Development of transgenics in Indian oilseed mustard (Brassica juncea) resistant to herbicide phosphinothricin. Curr Sci 78:1358–1364

    CAS  Google Scholar 

  • Moriyama EN, Powell JR (1997) Codon usage bias and tRNA abundance in Drosophila. J Mol Evol 45:514–523

    Article  CAS  PubMed  Google Scholar 

  • Nakamura Y, Gojobori T, Ikemura T (2000) Codon usage tabulated from international DNA sequence databases: status for the year 2000. Nucleic Acids Res 28:292. https://doi.org/10.1093/nar/28.1.292

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Peach C, Velten J (1991) Transgene expression variability (position effect) of CAT and GUS reporter genes driven by linked divergent T-DNA promoters. Plant Mol Biol 17:49–60

    Article  CAS  PubMed  Google Scholar 

  • Pechmann Frydman J (2013) Evolutionary conservation of codon optimality reveals hidden signatures of cotranslational folding. Nat Struct Mol Biol 20(2):237–243. https://doi.org/10.1038/nsmb.2466

    Article  CAS  PubMed  Google Scholar 

  • Perlak FJ, Fuchs RL, Dean DA, McPherson SL, Fischhoff DA (1991) Modification of the coding sequence enhances plant expression of insect control protein genes. Proc Natl Acad Sci 88(8):3324–3328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Plotkin JB, Kudla G (2011) Synonymous but not the same: the causes and consequences of codon bias. Nat Rev Genet 12:32–42. https://doi.org/10.1038/nrg2899

    Article  CAS  PubMed  Google Scholar 

  • Porceddu A, Zenoni S, Camiolo S (2013) The signatures of selection for translational accuracy in plant genes. Genome Biol. Evol 5:1117–1126. https://doi.org/10.1093/gbe/evt078

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Qian W, Yang J-R, Pearson NM, Maclean C, Zhang J (2012) Balanced Codon usage optimizes eukaryotic translational efficiency. PLoS Genet 8(3):e1002603. https://doi.org/10.1371/journal.pgen.1002603

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rawat P, Singh AK, Ray K, Chaudhary B, Kumar S, Gautam T, Kanoria S, Kaur G, Kumar P, Pental D, Burma PK (2011) Detrimental effect of expression of Bt endotoxin Cry1Ac on in vitro regeneration, in vivo growth and development of tobacco and cotton transgenics. J Biosci 36:363–376

    Article  CAS  PubMed  Google Scholar 

  • Rouwendal GJ, Mendes O, Wolbert EJ, Douwe de Boer A (1997) Enhanced expression in tobacco of the gene encoding green fluorescent protein by modification of its codon usage. Plant Mol Biol 33:989–999

    Article  CAS  PubMed  Google Scholar 

  • Shah P, Gilchrist MA (2011) Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift. Proc Natl Acad Sci USA 108:10231–10236. https://doi.org/10.1073/pnas.1016719108

    Article  PubMed  PubMed Central  Google Scholar 

  • Sharp PM, Tuohy TMF, Mosurski KR (1986) Codon usage in yeast cluster-analysis clearly Differentiates highly and lowly expressed genes. Nucleic Acids Res 14:5125–5143

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sinclair G, Choy FY (2002) Synonymous codon usage bias and the expression of human glucocerebrosidase in the methylotrophic yeast, Pichia pastoris. Protein Expr Purif 26(1):96–105

    Article  CAS  PubMed  Google Scholar 

  • Streatfield SJ (2007) Approaches to achieve high-level heterologous protein production in plants. Plant Biotechnol J 5(1):2–15

    Article  CAS  PubMed  Google Scholar 

  • Suo G, Chen B, Zhang J, Duan Z, He Z, Yao W, Yue C, Dai J (2006) Effects of codon modification on human BMP2 gene expression in tobacco plants. Plant Cell Rep 25:689–697

    Article  CAS  PubMed  Google Scholar 

  • Svab Z, Hajdukiewicz P, Maliga P (1995) Generation of transgenic tobacco plants by cocultivation of leaf disks with Agrobacterium pPZP binary vectors. In: Maliga P (ed) Methods in plant molecular biology: a laboratory course manual. Cold Spring Harbor Laboratory Press, Plainview, pp 55–77

    Google Scholar 

  • Thompson CJ, Movva NR, Tizard R, Grameri R, Davies JE, Lauwereys M, Botterman J (1987) Characterization of the herbicide-resistance gene bar from Streptomyces hygroscopicus. EMBO J 6:2519–2523

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Töpfer R, Matzeit V, Gronenborn B, Schell J, Steinbiss HH (1987) A set of plant expression vectors for transcriptional and translational fusions. Nucleic Acids Res 15(14):5890

    Article  PubMed  PubMed Central  Google Scholar 

  • Tuller T, Carmi A, Vestsigian K, Navon S, Dorfan Y, Zaborske J, Pan T, Dahan O, Furman I, Pilpel Y (2010a) An evolutionarily conserved mechanism for controlling the efficiency of protein translation. Cell 141:344–354. https://doi.org/10.1016/j.cell.2010.03.031

    Article  CAS  PubMed  Google Scholar 

  • Tuller T, Waldman YY, Kupiec M, Ruppin E (2010b) Translation efficiency is determined by both codon bias and folding energy. Proc Natl Acad Sci USA 107:3645–3650. https://doi.org/10.1073/pnas.0909910107

    Article  PubMed  PubMed Central  Google Scholar 

  • Wang L, Roossinck MJ (2006) Comparative analysis of expressed sequences reveals a conserved pattern of optimal codon usage in plants. Plant Mol Biol 61:699–710

    Article  CAS  PubMed  Google Scholar 

  • Welch M, Govindarajan S, Ness JE, Villalobos A, Gurney A, Minshull J, Gustafsson C (2009) Design parameters to control synthetic gene expression in Escherichia coli. PLoS ONE 4:e7002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wright SI, Yau CBK, Looseley M, Meyers BC (2004) Effects of gene expression on molecular evolution in Arabidopsis thaliana and Arabidopsis lyrata. Mol Biol Evol 21:1719–1726

    Article  CAS  PubMed  Google Scholar 

  • Wu G, ZhengY Qureshi I, Zin HT, Beck T, Bulka B, Freeland SJ (2007) SGDB: a database of synthetic genes re-designed for optimizing protein over-expression. Nucleic Acids Res 35:D76–D79

    Article  CAS  PubMed  Google Scholar 

  • Xu Y, Ma P, Shah P, Rokas A, Liu Y, Johnson CH (2013) Non-optimal codon usage is a mechanism to achieve circadian clock conditionality. Nature 495(7439):116–120. https://doi.org/10.1038/nature11942

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhou M, Guo J, Cha J, Chae M, Chen S, Barral JM, Sachs MS, Liu Y (2013) Non-optimal codon usage affects expression, structure and function of clock protein FRQ. Nature 495:111–115. https://doi.org/10.1038/nature11833

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhou Z, Dang Y, Zhou M, Li L, Yu C, Fu J, Chen S, Liu Y (2016) Codon usage is an important determinant of gene expression levels largely through its effects on transcription. Proc Natl Acad Sci USA 113:E6117–E6125. https://doi.org/10.1073/pnas.1606724113

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgement

The work was supported by grant in aids from University Grants Commission, India under their Special Assistance Program and from the University of Delhi. PA was supported by a fellowship from Council for Scientific and Industrial Research.

Author information

Authors and Affiliations

Authors

Contributions

PA and PKB conceived and designed the experiments, analyzed data and wrote the manuscript. PA carried out the experiments. TG and AKS contributed to plant transformation and Southern hybridization, respectively.

Corresponding author

Correspondence to Pradeep Kumar Burma.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agarwal, P., Gautam, T., Singh, A.K. et al. Evaluating the effect of codon optimization on expression of bar gene in transgenic tobacco plants. J. Plant Biochem. Biotechnol. 28, 189–202 (2019). https://doi.org/10.1007/s13562-019-00506-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13562-019-00506-2

Keywords

Navigation