# Decoding necrosome assembly: harmonizing signal amplification and attenuation through optimal RIP3 stoichiometry

## TL;DR

The study reveals how RIP3 and RIP1 proteins assemble in a precise ratio to control cell death signaling, preventing overactivation.

## Contribution

The paper identifies an optimal 3:1 RIP3 to RIP1 stoichiometry in necrosomes and shows how excessive RIP3 limits signaling.

## Key findings

- An approximately 3:1 RIP3 to RIP1 ratio in necrosomes optimizes signal amplification and threshold response.
- Excessive RIP3 oligomerization attenuates signaling, acting as an intrinsic size control mechanism.
- RIP3 assembly is dynamically regulated by stimulation, RIP1, and MLKL, ensuring efficient MLKL phosphorylation.

## Abstract

Necrosome assembly is essential for necroptosis, a process implicated in neurodegeneration, ischemic injury, and inflammatory diseases. Yet the spatiotemporal rules governing this assembly remain elusive. Leveraging quantitative STORM and mathematical modeling, we define an approximately 3:1 ratio of RIP3 to RIP1 in necrosomes as the optimal stoichiometry for necroptosis, enabling signal amplification and a threshold response. Surprisingly, excessive RIP3 oligomerization attenuates signaling, acting as an intrinsic size control mechanism. RIP3 assembly is dynamically regulated: it is constrained by stimulation and RIP1, promoted by RIP3 itself, and unexpectedly limited by downstream MLKL. A complementary balance between necrosome quantity and RIP3 assembly degree ensures efficient MLKL phosphorylation. In contrast, Caspase-8 assembly is limited by c-FLIP and recruited linearly by RIP1, while its distinct behavior from RIP3 underlies the biphasic necroptotic response to RIP1. These findings uncover the flexible, multi-strategic nature of signalosomes and offer valuable insights for therapeutic and synthetic biology.

Signalosomes amplify cellular responses, but how they avoid uncontrolled activation is unclear. The authors use quantitative super-resolution imaging and mathematical modeling to reveal optimal RIP3:RIP1 ratios that ensure precise cell death signaling.