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Interconnections between the Cation/Alkaline pH-Responsive Slt and the Ambient pH Response of PacC/Pal Pathways in Aspergillus nidulans .

Irene PicazoEduardo Antonio Espeso
Published in: Cells (2024)
In the filamentous ascomycete Aspergillus nidulans , at least three high hierarchy transcription factors are required for growth at extracellular alkaline pH: SltA, PacC and CrzA. Transcriptomic profiles depending on alkaline pH and SltA function showed that pacC expression might be under SltA regulation. Additional transcriptional studies of PacC and the only pH-regulated pal gene, palF , confirmed both the strong dependence on ambient pH and the function of SltA. The regulation of pacC expression is dependent on the activity of the zinc binuclear (C6) cluster transcription factor PacX. However, we found that the ablation of sltA in the pacX - mutant background specifically prevents the increase in pacC expression levels without affecting PacC protein levels, showing a novel specific function of the PacX factor. The loss of sltA function causes the anomalous proteolytic processing of PacC and a reduction in the post-translational modifications of PalF. At alkaline pH, in a null sltA background, PacC 72kDa accumulates, detection of the intermediate PacC 53kDa form is extremely low and the final processed form of 27 kDa shows altered electrophoretic mobility. Constitutive ubiquitination of PalF or the presence of alkalinity-mimicking mutations in pacC , such as pacC c 14 and pacC c 700 , resembling PacC 53kDa and PacC 27kDa , respectively, allowed the normal processing of PacC but did not rescue the alkaline pH-sensitive phenotype caused by the null sltA allele. Overall, data show that Slt and PacC/Pal pathways are interconnected, but the transcription factor SltA is on a higher hierarchical level than PacC on regulating the tolerance to the ambient alkalinity in A. nidulans .
Keyphrases
  • transcription factor
  • heat shock protein
  • binding protein
  • dna methylation
  • dna binding
  • sensitive detection
  • genome wide analysis