Analysis Of STK11/LKB1 Gene Using Bioinformatics Tools

Öz

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Anahtar Kelimeler

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Analysis Of STK11/LKB1 Gene Using Bioinformatics Tools

Öz

Aim: The STK11 gene, also known as LKB1, encodes for a serine/threonine kinase with growth-suppressing activity, such as inhibition of cell cycle progression, cell growth retardation, apoptotic cell death, and cell polarity control. This study aimed to investigate some properties of the STK11 gene and its product, such as the homologous protein sequences in different species, the common transcription factor binding sites on their promoters, their phylogenetic relationship, their catalytic domains (S_TKc), and their expression profiles. Methods: We investigated the homology, conserved domain, promoter and expression profiles of the STK11/LKB1 genes in various species using bioinformatics approaches. Results: Our results revealed that STK11/LKB1 molecules are conserved among all organisms investigated. The kinase domain (S_TKc) of human STK11/LKB1 gene is closest to those of Pan troglodytes, Macaca mulatta and Macaca fascicularis. In contrast, the most diverse to the human S_TKc domain is that of Bos taurus. With the multiple alignment strategy, protein and domain sequences of M. fascicularis and B. Taurus are predicted to have a truncation. The comparative screening of the promoters demonstrated that STK11/LKB1 genes do not seem to have any common conserved transcription factor binding sites. Conclusion: This study demonstrated STK11 molecules in various species are well conserved throughout evolution. Comparative screening of the promoter sequences of the human STK11 and its homologues found in the NCBI database revealed that there was no any common transcription factor binding sites. Phylogenetic trees constructed using the neighbor-joining method (NJ) revealed a close evolutionary relationship of S_TKc in various species

Anahtar Kelimeler

• LKB1, STK11, Bioinformatics, Comparative genomics, in silico biology

Kaynakça

1. Hemminki A, Tomlinson I, Markie D et al. Localization of a susceptibility locus for Peutz-Jeghers syndrome to 19p using comparative genomic hybridization and targeted linkage analysis. Nat Genet 1997;15(1):87-90
2. Nezu J, Oku A, Shimane M. Loss of cytoplasmic retention ability of mutant LKB1 found in Peutz-Jeghers syndrome patients. Biochem Biophys Res Commun 1999;261:750-5
3. Rowan A, Bataille V, MacKie R et al. Somatic Mutations in the Peutz- Jegners (LKB1/STKII) Gene in Sporadic Malignant Melanomas. J Invest Dermatol 1999;112:509–11
4. Tiainen M, Ylikorkala A, Makela TP. Growth suppression by Lkb1 is mediated by a G(1) cell cycle arrest. Proc Natl Acad Sci USA 1999;96(16):9248–51
5. Hearle NC, Tomlinson I, Lim W et al. Sequence changes in predicted promoter elements of STK11/LKB1 are unlikely to contribute to Peutz-Jeghers syndrome. BMC Genomics 2005; 6(38):1-5
6. Su JY, Erikson E, Maller JL. Cloning and characterization of a novel serine/ threonine protein kinase expressed in early Xenopus embryos. J Biol Chem 1996;271(24):14430-7
7. Smith DP, Spicer J, Smith A, Swift S, Ashworth A. The mouse Peutz- Jeghers syndrome gene Lkb1 encodes a nuclear protein kinase. Hum Mol Genet 1999;8(8):1479-85
8. Waterson RH, Lindblad-Toh K, Birney E et al. Initial sequencing and comparative analysis of the mouse genome. Nature 2002;420(6915):560–2

9. Boudeau J, Sapkota G, Alessi DR. LKB1, a protein kinase regulating cell proliferation and polarity. FEBS Lett 2003;546(1):159–65
10. Collins SP, Reoma JL, Gamm DM, Uhler MD. LKB1, a novel serine/threonine protein kinase and potential tumour suppressor, cAMP-dependent protein kinase (PKA) and prenylated in vivo. Biochem J 2000;345(1):673-80 NS, Clinicopathologic Features of Pancreatic Adenocarcinoma Associated with Peutz-Jeghers Syndrome. Cancer Biol Ther 2003;2(1):38-47 by 11. Yee Furth EE, and Molecular
11. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990;215(3):403-10
12. Gissen P, Johnson CA, Gentle D et al. Comparative evolutionary analysis of VPS33 homologues: genetic and functional insights. Hum Mol Genet 2005;14(10):1261–70
13. Thompson JD, Higgins DG, Gibson TJ. CLUSTALW: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position- specific gap penalties and weight matrix choice. Nucleic Acids Res 1994;22(22): 4673-80
14. Kumar S, Tamura K, and Nei M. MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence 2004;5(2):150-63 Brief Bioinf based on transcription
15. Hu Z, Chen K, Wang L, Yao Q. Identification and characterization of Bombyx mori eIF5A gene through bioinformatics approaches. In Silico Biol 2005;5(5-6):573-80
16. Varisli L, Cen O. Identification and Characterization of Rat GMDS Gene by Using Bioinformatics Tools. Turk J Biochem 2005;30(4):306-9