Protein homeostasis imprinting across evolution

Protein homeostasis (a.k.a. proteostasis) is associated with the primary functions of life, and therefore with evolution. However, it is unclear how the cellular proteostasis machines have evolved to adjust the protein biogenesis needs to environmental constraints. Herein, we describe a novel computational approach, based on semantic network analysis, to evaluate proteostasis differentiation during evolution. We show that the molecular components of the proteostasis network (PN) are reliable metrics to deconvolute the life forms into Archaea, Bacteria and Eukarya and to assess the evolution rates among species. Topological properties of semantic graphs were used as new criteria to evaluate PN complexity of 93 Eukarya, 250 Bacteria and 62 Archaea, thus representing a novel strategy for taxonomic classification. This functional analysis provides information about species divergence and pointed towards taxonomic clades that evolved faster than others. Kingdom-specific PN were identified, suggesting that PN complexity correlates evolution. Through the analysis of gene conservation, we found that the gains or losses that occurred throughout PN evolution revealed a dichotomy within both the PN conserved modules and within kingdom-specific modules. Since the PN is implicated in cell fitness, aging and disease onset, it could be used as a new metric to tackle mechanisms underlying gain-of-functions, and their biological ramifications.