Back

Integrated Dual-Channel Retrograde Signaling Directs Stress Responses by Degrading the HAT1/TPL/IMPalpha-9 Suppressor Complex and Activating CAMTA3

Zeng, L.; Guo, J.; Palayam, M.; Rodriguez, C.; Gomez Mendez, M. F.; Wang, Y.; Ven, W. v. d.; Pruneda-Paz, J.; Shabek, N.; Dehesh, K.

2024-08-30 plant biology
10.1101/2024.08.29.610327 bioRxiv
Show abstract

The intricate communication between plastids and the nucleus, shaping stress-responsive gene expression, has long intrigued researchers. This study combines genetics, biochemical analysis, cellular biology, and protein modeling to uncover how the plastidial metabolite MEcPP activates the stress-response regulatory hub known as the Rapid Stress Response Element (RSRE). Specifically, we identify the HAT1/TPL/IMP- 9 suppressor complex, where HAT1 directly binds to RSRE and its activator, CAMTA3, masking RSRE and sequestering the activator. Stress-induced MEcPP disrupts this complex, exposing RSRE and releasing CAMTA3, while enhancing Ca2+ influx and raising nuclear Ca2+levels crucial for CAMTA3 activation and the initiation of RSRE- containing gene transcription. This coordinated breakdown of the suppressor complex and activation of the activator highlights the dual-channel role of MEcPP in plastid-to- nucleus signaling. It further signifies how this metabolite transcends its expected biochemical role, emerging as a crucial initiator of harmonious signaling cascades essential for maintaining cellular homeostasis under stress. SummaryThis study uncovers how the stress-induced signaling metabolite MEcPP disrupts the HAT1/TPL/IMP-9 suppressor complex, liberating the activator CAMTA3 and enabling Ca2+ influx essential for CAMTA3 activation, thus orchestrating stress responses via repressor degradation and activator induction.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.