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Identification of the MAPK Cascade and its Relationship with Nitrogen Metabolism in the Green Alga Chlamydomonas reinhardtii.

Aitor Gomez-OsunaVictoria CalatravaAurora GalvánEmilio FernándezÁngel Llamas
Published in: International journal of molecular sciences (2020)
The mitogen activated protein kinases (MAPKs) form part of a signaling cascade through phosphorylation reactions conserved in all eukaryotic organisms. The MAPK cascades are mainly composed by three proteins, MAPKKKs, MAPKKs and MAPKs. Some signals induce MAPKKK-mediated phosphorylation and activation of MAPKK that phosphorylate and activate MAPK. Afterward, MAPKs can act either in the cytoplasm or be imported into the nucleus to activate other proteins or transcription factors. In the green microalga Chlamydomonas reinhardtii the pathway for nitrogen (N) assimilation is well characterized, yet its regulation still has many unknown features. Nitric oxide (NO) is a fundamental signal molecule for N regulation, where nitrate reductase (NR) plays a central role in its synthesis. The MAPK cascades could be regulating N assimilation, since it has been described that the phosphorylation of NR by MAPK6 promotes NO production in Arabidopsis thaliana. We have identified the proteins involved in the MAPK cascades in Chlamydomonas reinhardtii, finding 17 MAPKs, 2 MAPKKs and 108 MAPKKKs (11 MEKK-, 94 RAF- and 3 ZIK-type) that have been structurally and phylogenetically characterized. The genetic expressions of MAPKs and the MAPKK were slightly regulated by N. However, the genetic expressions of MAPKKKs RAF14 and RAF79 showed a very strong repression by ammonium, which suggests that they may have a key role in the regulation of N assimilation, encouraging to further analyze in detail the role of MAPK cascades in the regulation of N metabolism.
Keyphrases
  • signaling pathway
  • pi k akt
  • oxidative stress
  • nitric oxide
  • transcription factor
  • arabidopsis thaliana
  • gene expression
  • protein kinase
  • dna methylation
  • drinking water
  • gram negative
  • bioinformatics analysis