TY - JOUR TI - Stochastic yield catastrophes and robustness in self-assembly AU - Gartner, Florian M AU - Graf, Isabella R AU - Wilke, Patrick AU - Geiger, Philipp M AU - Frey, Erwin A2 - Jülicher, Frank A2 - Barkai, Naama A2 - Sartori, Pablo VL - 9 PY - 2020 DA - 2020/02/05 SP - e51020 C1 - eLife 2020;9:e51020 DO - 10.7554/eLife.51020 UR - https://doi.org/10.7554/eLife.51020 AB - A guiding principle in self-assembly is that, for high production yield, nucleation of structures must be significantly slower than their growth. However, details of the mechanism that impedes nucleation are broadly considered irrelevant. Here, we analyze self-assembly into finite-sized target structures employing mathematical modeling. We investigate two key scenarios to delay nucleation: (i) by introducing a slow activation step for the assembling constituents and, (ii) by decreasing the dimerization rate. These scenarios have widely different characteristics. While the dimerization scenario exhibits robust behavior, the activation scenario is highly sensitive to demographic fluctuations. These demographic fluctuations ultimately disfavor growth compared to nucleation and can suppress yield completely. The occurrence of this stochastic yield catastrophe does not depend on model details but is generic as soon as number fluctuations between constituents are taken into account. On a broader perspective, our results reveal that stochasticity is an important limiting factor for self-assembly and that the specific implementation of the nucleation process plays a significant role in determining the yield. KW - self-assembly KW - stochastic effects KW - yield optimization KW - mathematical modeling JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -