Guillaume Diss

Gene duplication can impart fragility, not robustness, in the yeast protein interaction network

Robustness of protein networks It is thought that gene duplication helps cells maintain genetic robustness, but this seems not to be the whole story. Diss et al. investigated the fate of protein-protein interactions among duplicated genes in yeast. Some interacting duplicates evolved mutual dependence, resulting in a more fragile system. This finding helps us understand the evolutionary trajectories of gene duplications and how seemingly redundant genes can increase the complexity of protein interaction networks. Science, this issue p. 630 Yeast gene duplicates illuminate the evolution of the protein-protein interaction network. The maintenance of duplicated genes is thought to protect cells from genetic perturbations, but the molecular basis of this robustness is largely unknown. By measuring the interaction of yeast proteins with their partners in wild-type cells and in cells lacking a paralog, we found that 22 out of 56 paralog pairs compensate for the lost interactions. An equivalent number of pairs exhibit the opposite behavior and require each other’s presence for maintaining their interactions. These dependent paralogs generally interact physically, regulate each other’s abundance, and derive from ancestral self-interacting proteins. This reveals that gene duplication may actually increase mutational fragility instead of robustness in a large number of cases.

Evidence for the Robustness of Protein Complexes to Inter-Species Hybridization

Despite the tremendous efforts devoted to the identification of genetic incompatibilities underlying hybrid sterility and inviability, little is known about the effect of inter-species hybridization at the protein interactome level. Here, we develop a screening platform for the comparison of protein–protein interactions (PPIs) among closely related species and their hybrids. We examine in vivo the architecture of protein complexes in two yeast species (Saccharomyces cerevisiae and Saccharomyces kudriavzevii) that diverged 5–20 million years ago and in their F1 hybrids. We focus on 24 proteins of two large complexes: the RNA polymerase II and the nuclear pore complex (NPC), which show contrasting patterns of molecular evolution. We found that, with the exception of one PPI in the NPC sub-complex, PPIs were highly conserved between species, regardless of protein divergence. Unexpectedly, we found that the architecture of the complexes in F1 hybrids could not be distinguished from that of the parental species. Our results suggest that the conservation of PPIs in hybrids likely results from the slow evolution taking place on the very few protein residues involved in the interaction or that protein complexes are inherently robust and may accommodate protein divergence up to the level that is observed among closely related species.

Systematic identification of signal integration by protein kinase A.

Significance Protein kinase A (PKA) complexes are versatile signaling enzymes controlling homeostasis in eukaryotes. This enzyme is involved in multiple functions under physiological and pathological conditions in humans and governs the virulence of many pathogenic fungi. Here we systematically identify PKA regulators in yeast. Notably, we describe signaling to PKA that involves feedback from the cellular recycling process, autophagy. We also uncover a posttranslational modification, acetylation, that regulates PKA activity in both yeast and mammals, and we show that this mechanism impacts aging. Thus, we identify what regulates PKA as a first step toward the ability to cure diseases and infections, for instance, by providing new candidate genes for drug targeting in health research and antifungals for agricultural and medical purposes. Cellular processes and homeostasis control in eukaryotic cells is achieved by the action of regulatory proteins such as protein kinase A (PKA). Although the outbound signals from PKA directed to processes such as metabolism, growth, and aging have been well charted, what regulates this conserved regulator remains to be systematically identified to understand how it coordinates biological processes. Using a yeast PKA reporter assay, we identified genes that influence PKA activity by measuring protein–protein interactions between the regulatory and the two catalytic subunits of the PKA complex in 3,726 yeast genetic-deletion backgrounds grown on two carbon sources. Overall, nearly 500 genes were found to be connected directly or indirectly to PKA regulation, including 80 core regulators, denoting a wide diversity of signals regulating PKA, within and beyond the described upstream linear pathways. PKA regulators span multiple processes, including the antagonistic autophagy and methionine biosynthesis pathways. Our results converge toward mechanisms of PKA posttranslational regulation by lysine acetylation, which is conserved between yeast and humans and that, we show, regulates protein complex formation in mammals and carbohydrate storage and aging in yeast. Taken together, these results show that the extent of PKA input matches with its output, because this kinase receives information from upstream and downstream processes, and highlight how biological processes are interconnected and coordinated by PKA.

Molecular mechanisms of paralogous compensation and the robustness of cellular networks.

Robustness is the ability of a system to maintain its function despite environmental or genetic perturbation. Genetic robustness is a key emerging property of living systems and is achieved notably by the presence of partially redundant parts that result from gene duplication. Functional overlap between paralogs allows them to compensate for each others loss, as commonly revealed by aggravating genetic interactions. However, the molecular mechanisms linking the genotype (loss of function of a gene) to the phenotype (genetic buffering by a paralog) are still poorly understood and the molecular aspects of this compensation are rarely addressed in studies of gene duplicates. Here, we review molecular mechanisms of functional compensation between paralogous genes, many of which from studies that were not meant to study this phenomenon. We propose a standardized terminology and, depending on whether or not the molecular behavior of the intact gene is modified in response to the deletion of its paralog, we classify mechanisms of compensation into passive and active events. We further describe three non-exclusive mechanisms of active paralogous compensation for which there is evidence in the literature: changes in abundance, in localization, and in protein interactions. This review will serve as a framework for the genetic and molecular analysis of paralogous compensation, one of the universal features of genetic systems.

Transcriptional divergence plays a role in the rewiring of protein interaction networks after gene duplication.

Gene duplication plays a key role in the evolution of protein-protein interaction (PPI) networks. After a gene duplication event, paralogous proteins may diverge through the gain and loss of PPIs. This divergence can be explained by two non-exclusive mechanisms. First, mutations may accumulate in the coding sequences of the paralogs and affect their protein sequences, which can modify, for instance, their binding interfaces and thus their interaction specificity. Second, mutations may accumulate in the non-coding region of the genes and affect their regulatory sequences. The resulting changes in expression profiles can lead to paralogous proteins being differentially expressed and occurring in the cell with different sets of potential interaction partners. These changes could also alter splicing regulation and lead to the inclusion or exclusion of alternative exons. The evolutionary role of these regulatory mechanisms remains largely unexplored. We use bioinformatics analyses of existing PPI data and proteome-wide PPI screening to show that the divergence of transcriptional regulation between paralogs plays a significant role in determining their PPI specificity. Because many gene duplication events are followed by rapid changes in transcriptional regulation, our results suggest that PPI networks may be rewired by gene duplication, without the need for protein to diverge in their binding specificities. This article is part of a Special Issue entitled: From protein structures to clinical applications.

Integrative avenues for exploring the dynamics and evolution of protein interaction networks.

Over the past decade, the study of protein interaction networks (PINs) has shed light on the organizing principles of living cells. However, PINs have been mostly mapped in one single condition. We outline three of the most promising avenues of investigation in this field, namely the study of first, how PINs are rewired by mutations and environmental perturbations; secondly, how inter-species interactions affect PIN achitectures; thirdly, what mechanisms and forces drive PIN evolution. These investigations will unravel the dynamics and condition dependence of PINs and will thus lead to a better functional annotation of network architecture. One major challenge to reach these goals is the integration of PINs with other cellular regulatory networks in the context of complex cellular phenotypes.

Modulation of the yeast protein interactome in response to DNA damage

UNLABELLED Cells deploy diverse mechanisms to physiologically adapt to potentially detrimental perturbations. These mechanisms include changes in the organization of protein-protein interaction networks (PINs). Most PINs characterized to date are portrayed in a single environmental condition and are thus likely to miss important connections among biological processes. In this report, we show that the yeast DHFR-PCA on high-density arrays allows to detects modulations of protein-protein interactions (PPIs) in different conditions by testing more than 1000 PPIs in standard and in a drug-inducing DNA damage conditions. We identify 156 PPIs that show significant modulation in response to DNA damage. We provide evidence that modulated PPIs involve essential genes (NOP7, EXO84 and LAS17) playing critical roles in response to DNA damage. Additionally, we show that a significant proportion of PPI changes are likely explained by changes in protein localization and, to a lesser extent, protein abundance. The protein interaction modules affected by changing PPIs support the role of mRNA stability and translation, protein degradation and ubiquitylation and the regulation of the actin cytoskeleton in response to DNA damage. Overall, we provide a valuable tool and dataset for the study of the rewiring of PINs in response to environmental perturbations. BIOLOGICAL SIGNIFICANCE We show that the DHFR-PCA is a high-throughput method that allows the detection of changes in PPIs associated with different environmental conditions using DNA damage response as a testbed. We provide a valuable resource for the study of DNA damage in eukaryotic cells. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

Biodiversity matters in a changing world.

It is now widely accepted that the climate of our planet is changing, but it is still hard to predict the consequences of these changes on ecosystems. The impact is worst at the poles, with scientists concerned that impacts at lower latitudes will follow suit. Canada has a great responsibility and potential for studying the effects of climate changes on the ecological dynamics, given its geographical location and its scientific leadership in this field. The 5th annual meeting of the Canadian Society for Ecology and Evolution was held in the International Year of Biodiversity, to share recent advances in a wide variety of disciplines ranging from molecular biology to behavioural ecology, and to integrate them into a general view that will help us preserve biodiversity and limit the impact of climate change on ecosystems.

The genetic landscape of a physical interaction

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions.

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells

Proteins are the building blocks, effectors and signal mediators of cellular processes. A protein’s function, regulation and localization often depend on its interactions with other proteins. Here, we describe a protocol for the yeast protein-fragment complementation assay (PCA), a powerful method to detect direct and proximal associations between proteins in living cells. The interaction between two proteins, each fused to a dihydrofolate reductase (DHFR) protein fragment, translates into growth of yeast strains in presence of the drug methotrexate (MTX). Differential fitness, resulting from different amounts of reconstituted DHFR enzyme, can be quantified on high-density colony arrays, allowing to differentiate interacting from non-interacting bait-prey pairs. The high-throughput protocol presented here is performed using a robotic platform that parallelizes mating of bait and prey strains carrying complementary DHFR-fragment fusion proteins and the survival assay on MTX. This protocol allows to systematically test for thousands of protein-protein interactions (PPIs) involving bait proteins of interest and offers several advantages over other PPI detection assays, including the study of proteins expressed from their endogenous promoters without the need for modifying protein localization and for the assembly of complex reporter constructs.