Protein abundances are more conserved than mRNA abundances across diverse taxa

Extensive divergence of yeast stress responses through transitions between induced and constitutive activation

Closely related species show a high degree of differences in gene expression, but the functional significance of these differences remains unclear. Similarly, stress responses in yeast typically involve differential expression of numerous genes, and it is unclear how many of these are functionally significant. To address these issues, we compared the expression programs of four yeast species under different growth conditions, and found that the response of these species to stress has diverged extensively. On an individual gene basis, most transcriptional responses are not conserved in any pair of species, and there are very limited common responses among all four species. We present evidence that many evolutionary changes in stress responses are compensated either (i) by the response of related genes or (ii) by changes in the basal expression levels of the genes whose responses have diverged. Thus, stress-related genes are often induced upon stress in some species but maintain high levels even in the absence of stress at other species, indicating a transition between induced and constitutive activation. In addition, ~15% of the stress responses are specific to only one of the four species, with no evidence for compensating effects or stress-related annotations, and these may reflect fortuitous regulation that is unimportant for the stress response (i.e., biological noise). Frequent compensatory changes and biological noise may explain how diverged expression responses support similar physiological responses.

Inferring regulatory mechanisms from patterns of evolutionary divergence

The number of sequenced species is increasing at a staggering rate, calling for new approaches for incorporating evolutionary information in the study of biological mechanisms. Evolutionary conservation is widely used for assigning a function to new proteins and for predicting functional coding or non-coding sequences. Here, we argue for a complementary approach that focuses on the divergence of regulatory programs. Regulatory mechanisms can be learned from patterns of evolutionary divergence in regulatory properties such as gene expression, transcription factor binding or nucleosome positioning. We review examples of this concept using yeast as a model system, and highlight a hybrid-based approach that is highly instrumental in this analysis.

Determinants of translation efficiency and accuracy

A given protein sequence can be encoded by an astronomical number of alternative nucleotide sequences. Recent research has revealed that this flexibility provides evolution with multiple ways to tune the efficiency and fidelity of protein translation and folding.

Proper functioning of biological cells requires that the process of protein expression be carried out with high efficiency and fidelity. Given an amino-acid sequence of a protein, multiple degrees of freedom still remain that may allow evolution to tune efficiency and fidelity for each gene under various conditions and cell types. Particularly, the redundancy of the genetic code allows the choice between alternative codons for the same amino acid, which, although ‘synonymous,' may exert dramatic effects on the process of translation. Here we review modern developments in genomics and systems biology that have revolutionized our understanding of the multiple means by which translation is regulated. We suggest new means to model the process of translation in a richer framework that will incorporate information about gene sequences, the tRNA pool of the organism and the thermodynamic stability of the mRNA transcripts. A practical demonstration of a better understanding of the process would be a more accurate prediction of the proteome, given the transcriptome at a diversity of biological conditions.

Scaffold-mediated nucleation of protein signaling complexes: elementary principles

Proteins with multiple binding sites play important roles in cell signaling systems by nucleating protein complexes in which, for example, enzymes and substrates are co-localized. Proteins that specialize in this function are called by a variety names, including adapter, linker and scaffold. Scaffold-mediated nucleation of protein complexes can be either constitutive or induced. Induced nucleation is commonly mediated by a docking site on a scaffold that is activated by phosphorylation. Here, by considering minimalist mathematical models, which recapitulate scaffold effects seen in more mechanistically detailed models, we obtain analytical and numerical results that provide insights into scaffold function. These results elucidate how recruitment of a pair of ligands to a scaffold depends on the concentrations of the ligands, on the binding constants for ligand-scaffold interactions, on binding cooperativity, and on the milieu of the scaffold, as ligand recruitment is affected by competitive ligands and decoy receptors. For the case of a bivalent scaffold, we obtain an expression for the unique scaffold concentration that maximally recruits a pair of monovalent ligands. Through simulations, we demonstrate that a bivalent scaffold can nucleate distinct sets of ligands to equivalent extents when the scaffold is present at different concentrations. Thus, the function of a scaffold can potentially change qualitatively with a change in copy number. We also demonstrate how a scaffold can change the catalytic efficiency of an enzyme and the sensitivity of the rate of reaction to substrate concentration. The results presented here should be useful for understanding scaffold function and for engineering scaffolds to have desired properties.

The aggregation properties of Escherichia coli proteins associated with their cellular abundance

Proteins are key players in most cellular processes. Therefore, their abundances are thought to be tightly regulated at the gene-expression level. Recent studies indicate, however, that steady-state cellular-protein concentrations correlate better across species than the levels of the corresponding mRNAs; this supports the existence of selective forces to maintain precise cellular-protein concentrations and homeostasis, even if gene-expression levels diverge. One of these forces might be the avoidance of protein aggregation because, in the cell, the folding of proteins into functional conformations might be in competition with anomalous aggregation into non-functional and usually toxic structures in a concentration-dependent manner. The data in the present work provide support for this hypothesis because, in E. coli, the experimental solubility of proteins correlates better with the cellular abundance than with the gene-expression levels. We found that the divergence between protein and mRNAs levels is low for high-abundance proteins. This suggests that because abundant proteins are at higher risk of aggregation, cellular concentrations need to be stringently regulated by gene expression.