hide
Free keywords:
-
Abstract:
Author summary Protein allocation determines the activity of cells and affects diverse traits across all organisms. However, prediction of protein allocation, particularly for conditions that do not result at optimal growth and physiology, remains a very challenging problem. In this study, we present an approach called PARROT to predict how cells allocate their proteins in different conditions. We tested different variants of PARROT by considering different objectives within a constraint-based formulation and by how much resource allocation information is used to guide predictions. We found that minimizing adjustments in protein allocation, rather than flux phenotypes, is a key principle that microorganisms use under alternative growth conditions. By integrating this principle into our approaches and leveraging quantitative proteomics data, PARROT provides more accurate predictions of protein allocation in unseen conditions in comparison to existing contenders. Therefore, PARROT can help in advancing our understanding of protein allocation under different conditions and its physiological implications. Further, we can gain valuable insights into cellular responses and adaptive strategies across different environments.
