• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Adaptivní evoluce Toll-like receptorů u ptáků / Adaptive evolution of Toll-like receptors in birds

Velová, Hana January 2020 (has links)
Adaptive evolution of Toll-like receptors in birds Hana Velová, PhD thesis 6 Abstract Toll-like receptors (TLRs) are one of the key and presumably also evolutionary most original components of animal immune system. As Pattern recognition receptors they form the first line of innate immune defence against various pathogens. The proper receptor binding of pathogenic ligands is crucial for their correct recognition and for subsequent triggering of an appropriate immune response. Because there exists a direct interaction between the receptor surface and the pathogenic ligand, host-pathogen coevolution on molecular level can be predicted. Thus, through variability of their ligands, TLRs are exposed to extensive selective pressures that may be detected on both genetic and protein levels. Surprisingly, the variability we revealed in birds is even higher than previously expected based on the reports from other vertebrates, mainly mammals. In my doctoral thesis I summarise the results of my contribution to the avian TLR research. We were the first who experimentally verify the absence of functional TLR5 in several avian species and duplication of TLR7 in others. We finally resolved the origin of duplication in TLR1 and in TLR2 family. An important part of my research project focused on the prediction of potentially...

Page generated in 0.08 seconds