The Second Language of DNA

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Resumo

DNA is crucial to life. This molecule rests at the heart of a cell nucleus, stands in between most important metabolic pathways, and provides the basis for genetic information flow. However does it really just rest? Is that big and early invention of evolution limited to the inert function of information storage? To address this we tackle several aspects of DNA structure. Each of them may become crucial when the molecule changes its role — when it serves as a blueprint for copying, a site for precise binding of proteins, or is involved in complex and dynamic interactions with them. We focus on promoters which initiate the process of transcription, i.e. the “rewriting” of DNA into RNA. Our setting is the tiny genome of bacteriophage T7 and its petite, very similar yet very distinct promoters.

Sobre autores

M. Orlov

Institute of Cell Biophysics, Pushchino Center for Biological Research, RAS

Email: orlovmikhailanat@gmail.com
Pushchino, Russia

Bibliografia

  1. Орлов М.А., Рясик А.А., Сорокин А.А. Дестабилизация дуплекса ДНК активно реплицирующихся промоторов бактериофагов группы Т7. Молекул. биол. 2018; 52(5): 793–800. doi: 10.1134/S0026898418050117.
  2. Орлов М.А., Камзолова С.Г., Рясик А.А. и др. Профили вызванной суперспирализацией дестабилизации дуплекса ДНК (SIDD) для промоторов бактериофага T7. Компьютерные исследования и моделирование. 2018; 6(10): 867–878. doi: 10.20537/2076-7633-2018-10-6-867-878.
  3. Koudelka G.B., Mauro S.A., Ciubotaru M. Indirect readout of DNA sequence by proteins: The roles of DNA sequence-dependent intrinsic and extrinsic forces. Progress in Nucleic Acid Research and Molecular Biology. 2006; 81: 143–177. doi: 10.1016/S0079-6603(06)81004-4.
  4. Schnepf M., von Reutern M., Ludwig C. et al. Transcription factor binding affinities and DNA shape readout. Science. 2020; 23(11): DOI:101694.10.1016/j.isci.2020.101694.
  5. Shahmuradov I.A., Razali R.M., Bougouffa S. et al. bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli. Bioinformatics. 2016; 33(3): 334–340. doi: 10.1093/bioinformatics/btw629.
  6. Wang H., Benham C.J. Promoter prediction and annotation of microbial genomes based on DNA sequence and structural responses to superhelical stress. BMC Bioinformatics. 2006; 7: 248. doi: 10.1186/1471-2105-7-248.
  7. Ryasik A., Orlov M., Zykova E. et al. Bacterial promoter prediction: Selection of dynamic and static physical properties of DNA for reliable sequence classification. J. Bioinform. Comput. Biol. 2018; 16(1): 1840003. doi: 10.1142/S0219720018400036.
  8. Kulczyk A.W., Richardson C.C. The Replication System of Bacteriophage T7. DNA Replication Across Taxa. 2016; 39: 89–136. doi: 10.1016/bs.enz.2016.02.001.
  9. Summers W.C. Bacteriophage T7. Fundamentals of Molecular Virology. N.H.Acheson (ed.). 2011; 2(7): 77.
  10. Орлов М.А. Текст и подтекст: физические свойства ДНК. Потенциал: химия. биология, медицина. 2020; 2: 13–23.
  11. Chen Z. Information theory based T7-like promoter models: classification of bacteriophages and differential evolution of promoters and their polymerases. Nucleic Acids Research. 2005; 33(19): 6172–6187. doi: 10.1093/nar/gki915.
  12. Сорокин А.А., Джелядин Т.Р., Орлов М.А. и др. Пространственная организация электростатических взаимодействий Т7 РНК-полимеразы с поздними промоторами Т7 ДНК. Вестник биотехнологии и физико-химической биологии имени Ю.А.Овчинникова. 2016; 12(4): 64–71.
  13. Orlov M., Garanina I., Fisunov G.Y., Sorokin A. Comparative analysis of Mycoplasma gallisepticum vlhA promoters. Front. Genet. 2018; 9: 569. doi: 10.3389/fgene.2018.00569.
  14. Komura R., Aoki W., Motone K. et al. High-throughput evaluation of T7 promoter variants using biased randomization and DNA barcoding. PLoS ONE. 2018; 13, e0196905. doi: 10.1371/journal.pone.0196905.
  15. Orlov M.A., Sorokin A.A. DNA sequence, physics, and promoter function: Analysis of high-throughput data On T7 promoter variants activity. J. Bioinform. Comput. Biol. 2020; 18: 2040001. doi: 10.1142/S0219720020400016.

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