5th International Young Scientist Congress (IYSC-2019).  International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Comparative study of Glycerate Kinase (GK): Bioinformatical Approach

Author Affiliations

  • 1 Department of Biotechnology, The University of Burdwan, Golapbag, Burdwan, 713104, West Bengal, INDIA

Int. Res. J. Biological Sci., Volume 2, Issue (12), Pages 50-59, December,10 (2013)

Abstract

There are three classes of Glycerate kinase (GK) which are class I GK, class II GK and class III GK. Class I and class II GKs produce glycerate 2-phosphate whereas class III GK (GLYK) only can produce glycerate 3-phosphate. Phylogenetic analysis on 16S ribosomal RNA sequences reveals the strong evolutionary relationship between cyanobacteria and plants. Phylogeny using GK DNA and amino acid sequences shows that cyanobacteria group is closely related with both bacteria and plants whereas fungi are closely related only with plants. Phylogeny using the amino acid sequence and hierarchical clustering on the basis of the amino acid frequencies of GK shows similar relationship among the taxa. Hierarchical clustering on the basis of GC% of GK encoding gene showing the unusual property like the RSCU value of the codons UUG and AGG are significantly low and CGA is significantly high in GC rich cluster. Correlation coefficient between GC% and the amino acids arginine, tryptophan and serine shows that the plants are different from the other selected species. ENc plot shows that except few GK genes from fungi and gammaproteobacteria all of them are under mutational bias. There is no as such codon usage similarity for the GK encoding gene from different organisms but they have similar degree of expression i.e, CAI (highest in plant) which is significantly low along with the amino acids lysine, phenylalanine, tyrosine, isoleusine and asparagine and serine in GC rich GK encoding gene.

References

  1. Boldt R., Edner C., Kolukisaoglu U., Hagemann M., Weckwerth W., Wienkoop S., Morgenthal K. and Bauwe, H., D-Glycerate 3-kinase, the last unknown enzyme in the photorespiratory cycle in Arabidopsis, belongs to a novel kinase family. Plant Cell, 17, 2413–2420 (2005)
  2. Hubbard B.K., Koch M., Palmer D.R., Babbitt P.C. and Gerlt J.A., Evolution of enzymatic activities in the enolase superfamily: characterization of the (D)-glucarate/galactarate catabolic pathway in Escherichia coli. Biochemistry, 37, 14369–14375 (1998)
  3. Aghaie A., Lechaplais C., Sirven P., Tricot S., Besnard- Gonnet M., Muselet D., de Berardinis V., Kreimeyer A., Gyapay G., Salanoubat M. and Perret A., New insights into the alternative D-glucarate degradation pathway, J. Biol. Chem., 283, 15638–15646 (2008)
  4. Cusa E., Obradors N., Baldoma L., Badia J. and Aguilar J., Genetic analysis of a chromosomal region containing genes required for assimilation of allantoin nitrogen and linked glyoxylate metabolism in Escherichia coli, J. Bacteriol, 181, 7479–7484 (1999)
  5. Bartsch O., Hagemann M., Bauwe H., Only plant –type (GLYK) glycerate kinases produce D-glycerate 3-phosphate. FEBS Lett., 582, 3025–3028 (2008)
  6. Reher M., Bott M., and Scho¨nheit P., Characterization of glycerate kinase (2-phosphoglycerate forming), a key enzyme of the nonphosphorylative Entner–Doudoroff pathway, from the thermoacidophilic euryarchaeon Picrophilus torridus. FEMS Microbiol. Lett., 259, 113–119 (2006)
  7. Van Schaftingen E., D-glycerate kinase deficiency as a cause of D-glyceric aciduria. FEBS Lett,.243, 127–131 (1989)
  8. Husic D.W., Husic H.D. and Tolbert N.E., The oxidative photosynthetic carbon cycle or C cycle, Crit. Rev. Plant Sci., 45–100 (1987)
  9. Eisenhut M., Ruth W., Haimovich M., Bauwea H., Kaplan A. and Hagemann M., The photorespiratory glycolate metabolism is essential for cyanobacteria and might have been conveyed endosymbiontically to plants, PNAS,105, 17199-17204 (2008)
  10. Deusch O., Landan G., Roettger M., Gruenheit N., Kowallik K.V., Allen J.F., Martin W. and Dagan T., Genes of cyanobacterial origin in plant nuclear genomes point to a heterocyst-forming plastid ancestor. Mol. Biol. Evol., 25, 748–761 (2008)
  11. Black S. and Wright N.G., Enzymatic formation of glyceryl and phosphoglyceryl methylthiol esters, J. Biol. Chem., 221, 171–180 (1956)
  12. Kleczkowski L.A., Randall D.D. and Zahler W.L., The substrate specificity, kinetics, and mechanism of glycerate-3- kinase from spinach leaves, Arch. Biochem. Biophys,236, 185–194 (1985)
  13. Bhattacharya A., Power J. and Davey M., Genetic Manipulation of Gibberellin (GA) Oxidase Genes in Nicotiana sylvestris using constitutive promoter to modify Plant Architecture, Res.J.Recent Sci., 1(5), 1-7 (2012)
  14. Maithri S.K., Ramesh K.V. and Mutangana D., Theoretical structure prediction of TcaA from Photorhabdus luminescens and aminopeptidase N receptor from Helicoverpa armigera, Res. J. Recent Sci., 2(2), 40-49 (2013)
  15. Bhatt T.K., Phylogenetic studies on tRNA dependent amidotransferase from Plasmodium falciparum, ISCA J.Biological Sci.,1(3), 20-24 (2012)
  16. Dwivedi V. D., Sharma T., Mishra Sarad K. and Pandey A.K., Insight to sequence information of lactoglutathione lyase enzyme from different source organism, I. Res. J. Biological Sci,1(6), 38-42 (2012)
  17. Kumar A. and Dwivedi V.D., Evolutionary analysis and motif discovery in rhodopsin from vertebrates, ISCA J.Biological Sci, 2(7), 6-11(2013)
  18. Felsenstein J., PHYLIP: Phylogeny interference package (version 3.69) Department of Genome Sciences and Department of Biology. University of Washington.Washington, USA), 164-166 (1989)
  19. Swofford D. L., Olsen G. J., Waddell P. J. and Hillis D. M., Phylogenetic inference. In D M Hillis, C Moritz and B K Mable (Eds.), Molecular systematics, Sunderland, USA: Sinauer Associates, Inc., Publishers. 2nd edn, 407-514 (1996)
  20. Mondal S. K., Shit S. and Kundu S., A comparative computational study of the ‘rbcL’ gene in plants and in the three prokaryotic families-Archaea, cyanobacteria and proteobacteria, IJBT, 12, 58-66 (2013)
  21. Saldanha A. J., Java Treeview-extensible visualization of microarray data. BIOINFORMATICS APPLICATIONS NOTE, 20(17), 3246–3248 (2004)
  22. Fu C., Xiong J. and Miao W., Genome wide identification and characterization of cytochrome P450 monooxygenase genes in the ciliat Tetrahymena thermophila, BMC genomics. 10, 208 (2009) doi: 10.1186/1471-2164-10-208 (2009)
  23. Meng Z., Wei L. and Xia L., Analysis of synonymous codon usage in chloroplast genome of Populus alba,J For Res.,19, 293-297 (2008)
  24. Sharp P. M., Tuohy T. M. F. and Mosurski, K. R., Codon usage in yeast: Cluster analysis clearly differentiates highly and lowly expressed genes, Nucleic Acids Research,14, 5125-5143 (1986)
  25. Kaufman L. and Rousseeuw P. J., Finding groups in data: An introduction to cluster analysis, John Wiley and Sons, Inc.New Jersey, USA) (1990)
  26. Sharma A. and Sharma P., Genetic and Phytochemical analysis of Cluster bean (Cyamopsis tetragonaloba (L.) Taub) by RAPD and HPLC, Res.J.Recent Sci.,2(2), 1-9 (2013)
  27. Sharp P. M. and Li W. H., The codon adaptation index a measure of directional synonymous codon usage bias, and its potential applications, Nucleic Acids Research,15, 1281-1295 (1987)