Protein misinteraction avoidance causes highly expressed proteins to evolve slowly

Key Laboratory of Gene Engineering of the Ministry of Education, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 03/2012; 109(14):E831-40. DOI: 10.1073/pnas.1117408109
Source: PubMed


The tempo and mode of protein evolution have been central questions in biology. Genomic data have shown a strong influence of the expression level of a protein on its rate of sequence evolution (E-R anticorrelation), which is currently explained by the protein misfolding avoidance hypothesis. Here, we show that this hypothesis does not fully explain the E-R anticorrelation, especially for protein surface residues. We propose that natural selection against protein-protein misinteraction, which wastes functional molecules and is potentially toxic, constrains the evolution of surface residues. Because highly expressed proteins are under stronger pressures to avoid misinteraction, surface residues are expected to show an E-R anticorrelation. Our molecular-level evolutionary simulation and yeast genomic analysis confirm multiple predictions of the hypothesis. These findings show a pluralistic origin of the E-R anticorrelation and reveal the role of protein misinteraction, an inherent property of complex cellular systems, in constraining protein evolution.

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    • "The expression level of a protein is one of the strongest predictors of protein sequence evolutionary rate; sequences of highly expressed proteins evolve more slowly than low-expression proteins (Duret and Mouchiroud 1999; Pal et al. 2001; Gout et al. 2010; Nabholz et al. 2013; Park et al. 2013; Yang et al. 2012). This relationship may be a function of specific selective constraints on sequences to avoid protein misfolding (Drummond et al. 2005; Geiler-Samerotte et al. 2011), protein misinteractions (Yang et al. 2012), a decrease in protein function (Gout et al. 2010; Cherry 2010), and/or mRNA misfolding (Park et al. 2013). Analyses of microarray data have shown that expression evolutionary rate is also negatively correlated with expression level across human and mouse orthologs (Liao and Zhang 2006). "
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    ABSTRACT: Protein expression level is one of the strongest predictors of protein sequence evolutionary rate, with high-expression protein sequences evolving at slower rates than low-expression protein sequences, largely because of constraints on protein folding and function. Expression evolutionary rates have also been shown to be negatively correlated with expression level across human and mouse orthologs over relatively long divergence times (i.e., approximately 100 million years). Long-term evolutionary patterns, however, often cannot be extrapolated to microevolutionary processes (and vice versa), and whether this relationship holds for traits evolving under directional selection within a single species over ecological timescales (i.e., <5,000 years) is unknown and not necessarily expected. Expression is a metabolically costly process, and the expression level of a particular protein is predicted to be a trade-off between the benefit of its function and the costs of its expression. Selection should drive the expression level of all proteins close to values that maximize fitness, particularly for high-expression proteins because of the increased energetic cost of production. Therefore, stabilizing selection may reduce the amount of standing expression variation for high-expression proteins and, in combination with physiological constraints that may place an upper-bound on the range of beneficial expression variation, these constraints could severely limit the availability of beneficial expression variants. To determine whether rapid expression evolution was restricted to low-expression proteins due to these constraints on highly expressed proteins over ecological timescales, we compared venom protein expression levels across mainland and island populations for three species of pit vipers. We detected significant differentiation in protein expression levels in two of the three species and found that rapid expression differentiation was restricted to low-expression proteins. Our results suggest that various constraints on high-expression proteins reduce the availability of beneficial expression variants relative to low-expression proteins, enabling low-expression proteins to evolve, and potentially lead to adaptation, more rapidly.
    Genetics 11/2015; DOI:10.1534/genetics.115.180547 · 5.96 Impact Factor
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    • "Based on Correspondence Analysis (CA) results, we observed the universal rule that functional factors (ESS and PPA) and transcriptional abundance (CAI and EL) were roughly grouped together, opposing the ERs in the second principal component (PC2, see Methods) (Additional file 1: Figure S1, Figure 4). Evolutionary constraints on highly transcribed proteins might prevent misfolding [7] or misinteraction [23]. This can hamper functionality and even potentially produce a large quantity of toxic proteins. "
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    ABSTRACT: Despite rapid progress in understanding the mechanisms that shape the evolution of proteins, the relative importance of various factors remain to be elucidated. In this study, we have assessed the effects of 16 different biological features on the evolutionary rates (ERs) of protein-coding sequences in bacterial genomes. Our analysis of 18 bacterial species revealed new correlations between ERs and constraining factors. Previous studies have suggested that transcriptional abundance overwhelmingly constrains the evolution of yeast protein sequences. This transcriptional abundance leads to selection against misfolding or misinteractions. In this study we found that there was no single factor in determining the evolution of bacterial proteins. Not only transcriptional abundance (codon adaptation index and expression level), but also protein-protein associations (PPAs), essentiality (ESS), subcellular localization of cytoplasmic membrane (SLM), transmembrane helices (TMH) and hydropathicity score (HS) independently and significantly affected the ERs of bacterial proteins. In some species, PPA and ESS demonstrate higher correlations with ER than transcriptional abundance. Different forces drive the evolution of protein sequences in yeast and bacteria. In bacteria, the constraints are involved in avoiding a build-up of toxic molecules caused by misfolding/misinteraction (transcriptional abundance), while retaining important functions (ESS, PPA) and maintaining the cell membrane (SLM, TMH and HS). Each of these independently contributes to the variation in protein evolution.
    BMC Evolutionary Biology 08/2013; 13(1):162. DOI:10.1186/1471-2148-13-162 · 3.37 Impact Factor
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    • "It is reasonable to assume that proteins having numerous binding partners experience stronger selective constraints than other proteins having fewer binding partners, all other aspects being equal. Therefore it is reasonable to expect a network's hub to evolve more slowly than the nodes of the network [82,83]. As such, we may expect that evolutionary innovations proceed through mutations in the less-connected nodes of the network (e.g. as demonstrated by Jeong et al. [41], that highly connected proteins are more essential for survival than fewer connected proteins). "
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