Abstract
Rice sulfite reductase (OsSiR) is important protein in reducing sulfite to sulfide. In this paper, it is aimed to shed light on OsSiR’s probable structure, function, and expression using in silico methods and test its responses under drought and salt stresses. Moreover, it was also analyzed if OsSiR was structurally different from other SiR proteins. We estimated that OsSiR lacks ribbon–helix–helix DNA-binding motif allowing it to bind to DNA; therefore, it was probably localized in stroma as a non-nucleoid-type protein. Also, we found that OsSiR expression was regulated by JA in roots and by crosstalk of JA and ABA in shoots. RT-qPCR results showed that there was 20% increase in the expression of OsSiR at 3rd h of the salt treatment. However, OsSiR was downregulated when exposed to drought stress and salt stress for longer periods of time, respectively. OsSiR has a high post-translational potential because of its high phosphorylation sites. This may be originating from the most prevalent residue, Gly, facilitating its binding to phosphates in OsSiR. Our docking results showed that ligand binding residues of OsSiR (Arg159, Thr162, Gln167, and Pro501) were also active site residues of OsSiR. Both two domains of OsSiR interacted with sulfite and the number of the residues in 4Fe–4S domain (PF01077) was higher. The findings in this study are important in terms of structural and expressional studies of rice SiR (OsSiR) and can be used for SiR proteins in sorghum (Sorghum bicolor), maize (Zea mays), and foxtail millet (Setaria italica), which are closely related and highly similar to OsSiR in terms of sequence and predicted 3D structure.
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References
Ardito F, Giuliani M, Perrone D et al (2017) The crucial role of protein phosphorylation in cell signalingand its use as targeted therapy (Review). Int J Mol Med 40:271–280. https://doi.org/10.3892/ijmm.2017.3036
Bailey TL, Boden M, Buske FA et al (2009) MEME suite: tools for motif discovery and searching. Nucleic Acids Res 37:202–208. https://doi.org/10.1093/nar/gkp335
Basu S, Roychoudhury A (2014) Expression profiling of abiotic stress-inducible genes in response to multiple stresses in rice (Oryza sativa L.) varieties with contrasting level of stress tolerance. Biomed Res Int. https://doi.org/10.1155/2014/706890
Benkert P, Tosatto SCE, Schomburg D (2008) QMEAN: a comprehensive scoring function for model quality assessment. Proteins Struct Funct Genet 71:261–277. https://doi.org/10.1002/prot.21715
Blom N, Gammeltoft S, Brunak S (1999) Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 294:1351–1362. https://doi.org/10.1006/jmbi.1999.3310
Bork C, Schwenn JD, Hell R (1998) Isolation and characterization of a gene for assimilatory sulfite reductase from Arabidopsis thaliana. Gene 212:147–153. https://doi.org/10.1016/S0378-1119(98)00155-3
Bustin SA, Benes V, Garson JA et al (2009) The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611–622. https://doi.org/10.1373/clinchem.2008.112797
Cao MJ, Wang Z, Zhao Q et al (2014) Sulfate availability affects ABA levels and germination response to ABA and salt stress in Arabidopsis thaliana. Plant J 77:604–615. https://doi.org/10.1111/tpj.12407
Chow C-N, Zheng H-Q, Wu N-Y et al (2016) PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants. Nucleic Acids Res 44:D1154–D1160. https://doi.org/10.1093/nar/gkv1035
El Sabagh A, Hossain A, Barutçular C et al (2020) Consequences of salinity stress on the quality of crops and its mitigation strategies for sustainable crop production: an outlook of arid and semi-arid regions. In: Fahad S, Hasanuzzaman M, Alam M et al (eds) Environment, climate, plant and vegetation growth. Springer Nature, Cham, pp 503–533
Fahad S, Hussain S, Bano A et al (2015) Potential role of phytohormones and plant growth-promoting rhizobacteria in abiotic stresses: consequences for changing environment. Environ Sci Pollut Res 22:4907–4921. https://doi.org/10.1007/s11356-014-3754-2
Finn RD, Coggill P, Eberhardt RY et al (2015) The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res 44:D279–D285. https://doi.org/10.1093/nar/gkv1344
Gabaldón T (2017) Evolution of proteins and proteomes: a phylogenetics approach. Evol Bioinforma 1:117693430500100. https://doi.org/10.1177/117693430500100004
Ghelis T, Bolbach G, Clodic G et al (2008) Protein tyrosine kinases and protein tyrosine phosphatases are involved in abscisic acid-dependent processes in arabidopsis seeds and suspension cells. Plant Physiol 148:1668–1680. https://doi.org/10.1104/pp.108.124594
Goodstein DM, Shu S, Howson R et al (2012) Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res 40:D1178–D1186. https://doi.org/10.1093/nar/gkr944
Gray IC, Barnes MR (2003) Amino acid properties and consequences of substitutions. In: Barnes MR, Gray IC (eds) Bioinformatics for geneticists, 1st edn. Wiley, Hoboken, pp 289–304
Gu H, Zhu P, Jiao Y et al (2011) PRIN: a predicted rice interactome network. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-12-161
Hall TATA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser 41:95–98. https://doi.org/10.1088/1751-8113/44/8/085201
Hasanuzzaman M, Bhuyan MHMB, Mahmud JA et al (2018) Interaction of sulfur with phytohormones and signaling molecules in conferring abiotic stress tolerance to plants. Plant Signal Behav 13:1–5. https://doi.org/10.1080/15592324.2018.1477905
Horton P, Park K-JK-J, Obayashi T et al (2007) WoLF PSORT: protein localization predictor. Nucleic Acids Res 35:W585–W587. https://doi.org/10.1093/nar/gkm259
Hu B, Jin J, Guo A-Y et al (2015) GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics 31:1296–1297. https://doi.org/10.1093/bioinformatics/btu817
Huey R, Garrett MM, Stefano F (2012) “Autodock vina.” Scripps Res Institute Mol Graph Lab La Jolla, California, pp 1–12
Jez JM, Ravilious GE, Herrmann J (2016) Structural biology and regulation of the plant sulfation pathway. Chem Biol Interact 259:31–38. https://doi.org/10.1016/j.cbi.2016.02.017
Kawabata T (2010) Detection of multiscale pockets on protein surfaces using mathematical morphology. Proteins Struct Funct Bioinforma 78:1195–1211. https://doi.org/10.1002/prot.22639
Khan MS, Haas FH, Samami AA et al (2010) Sulfite reductase defines a newly discovered bottleneck for assimilatory sulfate reduction and is essential for growth and development in Arabidopsis thaliana. Plant Cell 22:1216–1231. https://doi.org/10.1105/tpc.110.074088
Kim JH, Lim SD, Jang CS (2020) Oryza sativa drought-, heat-, and salt-induced RING finger protein 1 (OsDHSRP1) negatively regulates abiotic stress-responsive gene expression. Plant Mol Biol 103:235–252. https://doi.org/10.1007/s11103-020-00989-x
Kobayashi Y, Otani T, Ishibashi K et al (2016) C-terminal region of sulfite reductase is important to localize to chloroplast nucleoids in land plants. Genome Biol Evol 8:1459–1466. https://doi.org/10.1093/gbe/evw093
Koch O, Cole J, Klebe G (2008) Secbase—secondary structure elements and ligand binding. Chem Cent J 2:P21. https://doi.org/10.1186/1752-153x-2-s1-p21
Kopriva S (2006) Regulation of sulfate assimilation in Arabidopsis and beyond. Ann Bot 97:479–495. https://doi.org/10.1093/aob/mcl006
Kopriva S, Mugford SG, Matthewman C, Koprivova A (2009) Plant sulfate assimilation genes: redundancy versus specialization. Plant Cell Rep 28:1769–1780. https://doi.org/10.1007/s00299-009-0793-0
Koprivova A, Kopriva S (2016) Sulfation pathways in plants. Chem Biol Interact 259:23–30. https://doi.org/10.1016/j.cbi.2016.05.021
Krueger RJ, Siegel LM (1982) Evidence for siroheme-Fe4S4 interaction in spinach ferredoxin-sulfite reductase. Biochemistry 21:2905–2909. https://doi.org/10.1021/bi00541a015
Kumar S, Stecher G, Tamura K (2016) MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 33:1870–1874. https://doi.org/10.1093/molbev/msw054
Leustek T, Saito K (1999) Update on biochemistry sulfate transport and assimilation in plants 1. Ind Eng Chem 120:637–643
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods 25:402–408. https://doi.org/10.1006/meth.2001.1262
Nakayama M, Akashi T, Hase T (2000) Plant sulfite reductase: molecular structure, catalytic function and interaction with ferredoxin. J Inorg Biochem 82:27–32. https://doi.org/10.1016/S0162-0134(00)00138-0
Nguyen MN, Tan KP, Madhusudhan MS (2011) CLICK—topology-independent comparison of biomolecular 3D structures. Nucleic Acids Res 39:24–28. https://doi.org/10.1093/nar/gkr393
Orcan P, Isikalan C, Akbas F (2019) Evaluation of salinity tolerance in rice (Oryza Sativa L.) using water potential, biomass, membran damage and osmoprotective compound. Fresenius Environ Bull 28(4a):3313–3323
Patron NJ, Durnford DG, Kopriva S (2008) Sulfate assimilation in eukaryotes: Fusions, relocations and lateral transfers. BMC Evol Biol 8:1–14. https://doi.org/10.1186/1471-2148-8-39
Sato Y, Takehisa H, Kamatsuki K et al (2013) RiceXPro version 3.0: expanding the informatics resource for rice transcriptome. Nucleic Acids Res 41:D1206–D1213. https://doi.org/10.1093/nar/gks1125
Sekine K, Hase T, Sato N (2002) Reversible DNA compaction by sulfite reductase regulates transcriptional activity of chloroplast nucleoids. J Biol Chem 277:24399–24404
Selçuk İK, Işıkalan Ç, Akbaş F (2021) Physiological and biochemical responses of rice (Oryza sativa L.) varieties against drought. Bangladesh J Bot 50:335–342
Tian W, Chen C, Lei X et al (2018) CASTp 3.0: computed atlas of surface topography of proteins. Nucleic Acids Res 46:W363–W367. https://doi.org/10.1093/nar/gky473
Törönen P, Medlar A, Holm L (2018) PANNZER2: a rapid functional annotation web server. Nucleic Acids Res 46:W84–W88. https://doi.org/10.1093/nar/gky350
Trott O, Olson AJ (2010) Autodock vina: improving the speed and accuracy of docking. J Comput Chem 31:455–461. https://doi.org/10.1002/jcc.21334.AutoDock
Untergasser A, Cutcutache I, Koressaar T et al (2012) Primer3-new capabilities and interfaces. Nucleic Acids Res 40:1–12. https://doi.org/10.1093/nar/gks596
Wang M, Jia Y, Xu Z, Xia Z (2016) Impairment of sulfite reductase decreases oxidative stress tolerance in Arabidopsis thaliana. Front Plant Sci 7:1–10. https://doi.org/10.3389/fpls.2016.01843
Whisstock JC, Lesk AM (2003) Prediction of protein function from protein sequence and structure. Q Rev Biophys 36:307–340. https://doi.org/10.1017/S0033583503003901
Willard L, Ranjan A, Zhang H et al (2003) VADAR: a web server for quantitative evaluation of protein structure quality. Nucleic Acids Res 31:3316–3319. https://doi.org/10.1093/nar/gkg565
Xia L, Zou D, Sang J et al (2017) Rice expression database (RED): an integrated RNA-seq-derived gene expression database for rice. J Genet Genomics 44:235–241. https://doi.org/10.1016/j.jgg.2017.05.003
Xia Z, Wang M, Xu Z (2018) The maize sulfite reductase is involved in cold and oxidative stress responses. Front Plant Sci 871:1–13. https://doi.org/10.3389/fpls.2018.01680
Xu J, Zhang Y (2010) How significant is a protein structure similarity with TM-score = 0.5? Bioinformatics 26:889–895. https://doi.org/10.1093/bioinformatics/btq066
Yang J, Yan R, Roy A et al (2015) The I-TASSER suite: protein structure and function prediction. Nat Methods 12:7–8. https://doi.org/10.1038/nmeth.3213
Yarmolinsky D, Brychkova G, Fluhr R, Sagi M (2013) Sulfite reductase protects plants against sulfite toxicity. Plant Physiol 161:725–743. https://doi.org/10.1104/pp.112.207712
Yarmolinsky D, Brychkova G, Kurmanbayeva A et al (2014) Impairment in sulfite reductase leads to early leaf senescence in tomato plants. Plant Physiol 165:1505–1520. https://doi.org/10.1104/pp.114.241356
Zhang Z, Li Y, Lin B et al (2011) Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction. Bioinformatics 27:2083–2088. https://doi.org/10.1093/bioinformatics/btr331
Zuckerkandl E, Pauling L (1965) Molecules as documents of history. J Theor Biol 8:357–366. https://doi.org/10.1016/0022-5193(65)90083-4
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Authors thanks Muş Alparslan University for providing Workstation under Faculty of Applied Sciences to conduct docking analyses.
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EF and FK designed the study. EF, FK, and AA conducted the experiments and analyzed the data. All authors contributed to writing and editing the manuscript.
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Kurt, F., Filiz, E. & Aydın, A. Sulfite Reductase (SiR) Gene in Rice (Oryza sativa): Bioinformatics and Expression Analyses Under Salt and Drought Stresses. J Plant Growth Regul 41, 2246–2260 (2022). https://doi.org/10.1007/s00344-021-10438-8
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DOI: https://doi.org/10.1007/s00344-021-10438-8